A B C D E F G H I L M N O P Q R S T U W X Y

A

a - Variable in class regression.Regress
 
anchor - Variable in class rubberband.Rubberband
 
anchor(Point) - Method in class rubberband.Rubberband
 
atof(String) - Static method in class corejava.Format
Converts a string of digits to an double
atoi(String) - Static method in class corejava.Format
Converts a string of digits (decimal, octal or hex) to an integer
atol(String) - Static method in class corejava.Format
Converts a string of digits (decimal, octal or hex) to a long integer

B

b - Variable in class regression.Regress
 
bakslv_f77(int, double[][], double[], double[]) - Static method in class optimization.Uncmin_f77
The bakslv_f77 method solves Ax = b where A is an upper triangular matrix.
Blas_f77 - class linear_algebra.Blas_f77.
This class contains Java versions of a number of the LINPACK basic linear algebra subroutines (blas): isamax_f77 daxpy_f77 ddot_f77 dscal_f77 dswap_f77 dnrm2_f77 dcopy_f77 drotg_f77 It also contains utility routines that the translator found useful while translating the FORTRAN code to Java code.
Blas_f77() - Constructor for class linear_algebra.Blas_f77
 
Blas_j - class linear_algebra.Blas_j.
This class contains Java versions of a number of the LINPACK basic linear algebra subroutines (blas): isamax_j daxpy_j ddot_j dscal_j dswap_j dnrm2_j dcopy_j drotg_j It also contains utility routines that the translator found useful while translating the FORTRAN code to Java code.
Blas_j() - Constructor for class linear_algebra.Blas_j
 
bounds() - Method in class rubberband.Rubberband
 
box(Graphics, double, double, double, double) - Method in class SPV_graphics.SPVGrint
DrawRect that uses world coordinates rather than pixel coordinates.

C

CDF_nct_Amos - class distributions.CDF_nct_Amos.
This class contains Java translations of FORTRAN routines written by Don Amos and S.L.
CDF_nct_Amos() - Constructor for class distributions.CDF_nct_Amos
 
CDF_Normal - class distributions.CDF_Normal.
This class contains routines to calculate the normal cumulative distribution function (CDF) and its inverse.
CDF_Normal_Amos - class distributions.CDF_Normal_Amos.
This class contains a Java translation of a FORTRAN routine written by Don Amos and S.L.
CDF_Normal_Amos_Test - class distributions.CDF_Normal_Amos_Test.
This class tests the CDF_Normal_Amos class.
CDF_Normal_Amos_Test() - Constructor for class distributions.CDF_Normal_Amos_Test
 
CDF_Normal_Amos() - Constructor for class distributions.CDF_Normal_Amos
 
CDF_Normal_Test - class distributions.CDF_Normal_Test.
This class tests the CDF_Normal class.
CDF_Normal_Test() - Constructor for class distributions.CDF_Normal_Test
 
CDF_Normal() - Constructor for class distributions.CDF_Normal
 
CDF_Weibull2 - class distributions.CDF_Weibull2.
Currently, this class contains methods to calculate the cumulative distribution function (CDF) of a 2-parameter Weibull distribution and the inverse of the CDF.
CDF_Weibull2_Test - class distributions.CDF_Weibull2_Test.
This class tests the CDF_Weibull2 class.
CDF_Weibull2_Test() - Constructor for class distributions.CDF_Weibull2_Test
 
CDF_Weibull2() - Constructor for class distributions.CDF_Weibull2
 
CDF_Weibull3 - class distributions.CDF_Weibull3.
Currently, this class contains methods to calculate the cumulative distribution function (CDF) of a 3-parameter Weibull distribution and the inverse of the CDF.
CDF_Weibull3_Test - class distributions.CDF_Weibull3_Test.
This class tests the CDF_Weibull3 class.
CDF_Weibull3_Test() - Constructor for class distributions.CDF_Weibull3_Test
 
CDF_Weibull3() - Constructor for class distributions.CDF_Weibull3
 
chlhsn_f77(int, double[][], double, double[], double[]) - Static method in class optimization.Uncmin_f77
The chlhsn_f77 method finds "THE L(L-TRANSPOSE) [WRITTEN LL+] DECOMPOSITION OF THE PERTURBED MODEL HESSIAN MATRIX A+MU*I(WHERE MU\0 AND I IS THE IDENTITY MATRIX) WHICH IS SAFELY POSITIVE DEFINITE.
choldc_f77(int, double[][], double, double, double[]) - Static method in class optimization.Uncmin_f77
The choldc_f77 method finds "THE PERTURBED L(L-TRANSPOSE) [WRITTEN LL+] DECOMPOSITION OF A+D, WHERE D IS A NON-NEGATIVE DIAGONAL MATRIX ADDED TO A IF NECESSARY TO ALLOW THE CHOLESKY DECOMPOSITION TO CONTINUE." Translated by Steve Verrill, April 15, 1998.
Cholesky - class linear_algebra.Cholesky.
This class contains: a method that obtains the Cholesky factorization RR´, where R is a lower triangular matrix, of a symmetric positive definite matrix A.
Cholesky_f77 - class linear_algebra.Cholesky_f77.
This class contains the LINPACK DPOFA (Cholesky decomposition), DPOSL (solve), and DPODI (determinant and inverse) routines.
Cholesky_f77() - Constructor for class linear_algebra.Cholesky_f77
 
Cholesky_j - class linear_algebra.Cholesky_j.
This class contains the LINPACK DPOFA (Cholesky decomposition), DPOSL (solve), and DPODI (determinant and inverse) routines.
Cholesky_j() - Constructor for class linear_algebra.Cholesky_j
 
Cholesky() - Constructor for class linear_algebra.Cholesky
 
CholTest - class linear_algebra.CholTest.
This class tests the Cholesky decomposition class and the Triangular solve/invert class.
CholTest_f77 - class linear_algebra.CholTest_f77.
This class tests the Cholesky_f77 classes.
CholTest_f77() - Constructor for class linear_algebra.CholTest_f77
 
CholTest_j - class linear_algebra.CholTest_j.
This class tests the Cholesky_j classes.
CholTest_j() - Constructor for class linear_algebra.CholTest_j
 
CholTest() - Constructor for class linear_algebra.CholTest
 
colaxpy_f77(int, double, double[][], int, int, int) - Static method in class linear_algebra.Blas_f77
This method multiplies a constant times a portion of a column of a matrix and adds the product to the corresponding portion of another column of the matrix --- a portion of col2 is replaced by the corresponding portion of a*col1 + col2.
colaxpy_j(int, double, double[][], int, int, int) - Static method in class linear_algebra.Blas_j
This method multiplies a constant times a portion of a column of a matrix and adds the product to the corresponding portion of another column of the matrix --- a portion of col2 is replaced by the corresponding portion of a*col1 + col2.
coldot_f77(int, double[][], int, int, int) - Static method in class linear_algebra.Blas_f77
This method calculates the dot product of portions of two columns of a matrix.
coldot_j(int, double[][], int, int, int) - Static method in class linear_algebra.Blas_j
This method calculates the dot product of portions of two columns of a matrix.
colisamax_f77(int, double[][], int, int, int) - Static method in class linear_algebra.Blas_f77
This method finds the index of the element of a portion of a column of a matrix that has the maximum absolute value.
colisamax_j(int, double[][], int, int, int) - Static method in class linear_algebra.Blas_j
This method finds the index of the element of a portion of a column of a matrix that has the maximum absolute value.
colnrm2_f77(int, double[][], int, int) - Static method in class linear_algebra.Blas_f77
This method calculates the Euclidean norm of a portion of a column of a matrix.
colnrm2_j(int, double[][], int, int) - Static method in class linear_algebra.Blas_j
This method calculates the Euclidean norm of a portion of a column of a matrix.
colrot_f77(int, double[][], int, int, double, double) - Static method in class linear_algebra.Blas_f77
This method "applies a plane rotation." It is a modification of the LINPACK function DROT.
colrot_j(int, double[][], int, int, double, double) - Static method in class linear_algebra.Blas_j
This method "applies a plane rotation." It is a modification of the LINPACK function DROT.
colscal_f77(int, double, double[][], int, int) - Static method in class linear_algebra.Blas_f77
This method scales a portion of a column of a matrix by a constant.
colscal_j(int, double, double[][], int, int) - Static method in class linear_algebra.Blas_j
This method scales a portion of a column of a matrix by a constant.
colswap_f77(int, double[][], int, int) - Static method in class linear_algebra.Blas_f77
This method interchanges two columns of a matrix.
colswap_j(int, double[][], int, int) - Static method in class linear_algebra.Blas_j
This method interchanges two columns of a matrix.
colvaxpy_f77(int, double, double[][], double[], int, int) - Static method in class linear_algebra.Blas_f77
This method multiplies a constant times a portion of a column of a matrix x[ ][ ] and adds the product to the corresponding portion of a vector y[ ] --- a portion of y[ ] is replaced by the corresponding portion of ax[ ][j] + y[ ].
colvaxpy_j(int, double, double[][], double[], int, int) - Static method in class linear_algebra.Blas_j
This method multiplies a constant times a portion of a column of a matrix x[ ][ ] and adds the product to the corresponding portion of a vector y[ ] --- a portion of y[ ] is replaced by the corresponding portion of ax[ ][j] + y[ ].
colvdot_f77(int, double[][], double[], int, int) - Static method in class linear_algebra.Blas_f77
This method calculates the dot product of a portion of a column of a matrix and the corresponding portion of a vector.
colvdot_j(int, double[][], double[], int, int) - Static method in class linear_algebra.Blas_j
This method calculates the dot product of a portion of a column of a matrix and the corresponding portion of a vector.
colvraxpy_f77(int, double, double[], double[][], int, int) - Static method in class linear_algebra.Blas_f77
This method multiplies a constant times a portion of a vector y[ ] and adds the product to the corresponding portion of a column of a matrix x[ ][ ] --- a portion of column j of x[ ][ ] is replaced by the corresponding portion of ay[ ] + x[ ][j].
colvraxpy_j(int, double, double[], double[][], int, int) - Static method in class linear_algebra.Blas_j
This method multiplies a constant times a portion of a vector y[ ] and adds the product to the corresponding portion of a column of a matrix x[ ][ ] --- a portion of column j of x[ ][ ] is replaced by the corresponding portion of ay[ ] + x[ ][j].
Console - class corejava.Console.
 
Console() - Constructor for class corejava.Console
 
corejava - package corejava
 
corr(double[], double[], int) - Method in class tests_of_fit.W3PP
This routine calculates the value of a correlation goodness-of-fit test statistic.
corr(double[], double[], int) - Method in class tests_of_fit.W2PP
This routine calculates the value of a correlation goodness-of-fit test statistic.

D

daxpy_f77(int, double, double[], int, double[], int) - Static method in class linear_algebra.Blas_f77
This method multiplies a constant times a vector and adds the product to another vector --- dy[ ] = da*dx[ ] + dy[ ].
daxpy_j(int, double, double[], int, double[], int) - Static method in class linear_algebra.Blas_j
This method multiplies a constant times a vector and adds the product to another vector --- dy[ ] = da*dx[ ] + dy[ ].
dcopy_f77(int, double[], int, double[], int) - Static method in class linear_algebra.Blas_f77
This method copies the vector dx[ ] to the vector dy[ ].
dcopy_j(int, double[], int, double[], int) - Static method in class linear_algebra.Blas_j
This method copies the vector dx[ ] to the vector dy[ ].
dcopyp_f77(int, double[], double[], int) - Static method in class linear_algebra.Blas_f77
This method copies a portion of vector x[ ] to the corresponding portion of vector y[ ].
dcopyp_j(int, double[], double[], int) - Static method in class linear_algebra.Blas_j
This method copies a portion of vector x[ ] to the corresponding portion of vector y[ ].
dcsevl(double, double[], int) - Static method in class distributions.Derf
This method evaluates the n-term Chebyshev series cs at x.
ddot_f77(int, double[], int, double[], int) - Static method in class linear_algebra.Blas_f77
This method calculates the dot product of two vectors.
ddot_j(int, double[], int, double[], int) - Static method in class linear_algebra.Blas_j
This method calculates the dot product of two vectors.
Derf - class distributions.Derf.
This class contains a Java translation of FORTRAN routines written by W.
Derf() - Constructor for class distributions.Derf
 
derf(double) - Static method in class distributions.Derf
This method calculates the double precision error function.
derfc(double) - Static method in class distributions.Derf
This method calculates the double precision complementary error function.
DerfTest - class distributions.DerfTest.
This class tests the Derf class.
DerfTest() - Constructor for class distributions.DerfTest
 
dfault_f77(int, double[], double[], double[], int[], int[], int[], int[], int[], int[], int[], double[], double[], double[], double[]) - Static method in class optimization.Uncmin_f77
The dfault_f77 method sets default values for each input variable to the minimization algorithm.
dgedi_f77(double[][], int, int[], double[], double[], int) - Static method in class linear_algebra.LU_f77
This method uses the LU decomposition provided by DGEFA to obtain the determinant and/or inverse of a full rank n by n matrix.
dgedi_j(double[][], int, int[], double[], double[], int) - Static method in class linear_algebra.LU_j
This method uses the LU decomposition provided by DGEFA to obtain the determinant and/or inverse of a full rank n by n matrix.
dgefa_f77(double[][], int, int[]) - Static method in class linear_algebra.LU_f77
This method decomposes an n by n matrix A into a product, LU, where L is a lower triangular matrix and U is an upper triangular matrix.
dgefa_j(double[][], int, int[]) - Static method in class linear_algebra.LU_j
This method decomposes an n by n matrix A into a product, LU, where L is a lower triangular matrix and U is an upper triangular matrix.
dgesl_f77(double[][], int, int[], double[], int) - Static method in class linear_algebra.LU_f77
This method uses the LU decomposition provided by DGEFA to solve the equation Ax = b where A is a full rank n by n matrix.
dgesl_j(double[][], int, int[], double[], int) - Static method in class linear_algebra.LU_j
This method uses the LU decomposition provided by DGEFA to solve the equation Ax = b where A is a full rank n by n matrix.
distributions - package distributions
 
dnrm2_f77(int, double[], int) - Static method in class linear_algebra.Blas_f77
This method calculates the Euclidean norm of the vector stored in dx[ ] with storage increment incx.
dnrm2_j(int, double[], int) - Static method in class linear_algebra.Blas_j
This method calculates the Euclidean norm of the vector stored in dx[ ] with storage increment incx.
dnrm2p_f77(int, double[], int) - Static method in class linear_algebra.Blas_f77
This method calculates the Euclidean norm of a portion of a vector x[ ].
dnrm2p_j(int, double[], int) - Static method in class linear_algebra.Blas_j
This method calculates the Euclidean norm of a portion of a vector x[ ].
dogdrv_f77(int, double[], double[], double[], double[][], double[], double[], double[], Uncmin_methods, double[], double[], double[], double[], int[], boolean[], double[], double[], double[], double[]) - Static method in class optimization.Uncmin_f77
The dogdrv_f77 method finds the next Newton iterate (xpls) by the double dogleg method.
dogstp_f77(int, double[], double[][], double[], double[], double, double[], boolean[], boolean[], double[], double[], double[], double[], double[], double[]) - Static method in class optimization.Uncmin_f77
The dogstp_f77 method finds the new step by the double dogleg appproach.
dpodi_f77(double[][], int, double[], int) - Static method in class linear_algebra.Cholesky_f77
This method uses the Cholesky decomposition provided by DPOFA to obtain the determinant and/or inverse of a symmetric, positive definite matrix.
dpodi_j(double[][], int, double[], int) - Static method in class linear_algebra.Cholesky_j
This method uses the Cholesky decomposition provided by DPOFA to obtain the determinant and/or inverse of a symmetric, positive definite matrix.
dpofa_f77(double[][], int) - Static method in class linear_algebra.Cholesky_f77
This method decomposes an p by p symmetric, positive definite matrix X into a product, R´R, where R is an upper triangular matrix and R´ is the transpose of R.
dpofa_j(double[][], int) - Static method in class linear_algebra.Cholesky_j
This method decomposes an p by p symmetric, positive definite matrix X into a product, R´R, where R is an upper triangular matrix and R´ is the transpose of R.
dposl_f77(double[][], int, double[]) - Static method in class linear_algebra.Cholesky_f77
This method uses the Cholesky decomposition provided by DPOFA to solve the equation Ax = b where A is symmetric, positive definite.
dposl_j(double[][], int, double[]) - Static method in class linear_algebra.Cholesky_j
This method uses the Cholesky decomposition provided by DPOFA to solve the equation Ax = b where A is symmetric, positive definite.
dqrdc_f77(double[][], int, int, double[], int[], double[], int) - Static method in class linear_algebra.QR_f77
This method decomposes an n by p matrix X into a product, QR, of an orthogonal n by n matrix Q and an upper triangular n by p matrix R.
dqrdc_j(double[][], int, int, double[], int[], double[], int) - Static method in class linear_algebra.QR_j
This method decomposes an n by p matrix X into a product, QR, of an orthogonal n by n matrix Q and an upper triangular n by p matrix R.
dqrsl_f77(double[][], int, int, double[], double[], double[], double[], double[], double[], double[], int) - Static method in class linear_algebra.QR_f77
This method "applies the output of DQRDC to compute coordinate transformations, projections, and least squares solutions." For details, see the comments in the code.
dqrsl_j(double[][], int, int, double[], double[], double[], double[], double[], double[], double[], int) - Static method in class linear_algebra.QR_j
This method "applies the output of DQRDC to compute coordinate transformations, projections, and least squares solutions." For details, see the comments in the code.
drawLast(Graphics) - Method in class rubberband.RubberbandRectangleX
 
drawLast(Graphics) - Method in class rubberband.RubberbandRectangle
 
drawLast(Graphics) - Method in class rubberband.Rubberband
 
drawNext(Graphics) - Method in class rubberband.RubberbandRectangleX
 
drawNext(Graphics) - Method in class rubberband.RubberbandRectangle
 
drawNext(Graphics) - Method in class rubberband.Rubberband
 
drotg_f77(double[]) - Static method in class linear_algebra.Blas_f77
This method constructs a Givens plane rotation.
drotg_j(double[]) - Static method in class linear_algebra.Blas_j
This method constructs a Givens plane rotation.
dscal_f77(int, double, double[], int) - Static method in class linear_algebra.Blas_f77
This method scales a vector by a constant.
dscal_j(int, double, double[], int) - Static method in class linear_algebra.Blas_j
This method scales a vector by a constant.
dscalp_f77(int, double, double[], int) - Static method in class linear_algebra.Blas_f77
This method scales a portion of a vector by a constant.
dscalp_j(int, double, double[], int) - Static method in class linear_algebra.Blas_j
This method scales a portion of a vector by a constant.
dsvdc_f77(double[][], int, int, double[], double[], double[][], double[][], double[], int) - Static method in class linear_algebra.SVDC_f77
This method decomposes a n by p matrix X into a product UDV´ where ...
dsvdc_j(double[][], int, int, double[], double[], double[][], double[][], double[], int) - Static method in class linear_algebra.SVDC_j
This method decomposes a n by p matrix X into a product UDV´ where ...
dswap_f77(int, double[], int, double[], int) - Static method in class linear_algebra.Blas_f77
This method interchanges two vectors.
dswap_j(int, double[], int, double[], int) - Static method in class linear_algebra.Blas_j
This method interchanges two vectors.

E

ECDF - class tests_of_fit.ECDF.
This class returns the x,y for an empirical cumulative distribution function.
ECDF() - Constructor for class tests_of_fit.ECDF
 
end - Variable in class rubberband.Rubberband
 
end(Point) - Method in class rubberband.Rubberband
 
enorm_f77(int, double[]) - Static method in class optimization.Minpack_f77
The enorm_f77 method calculates the Euclidean norm of a vector.

F

f_to_integrate(double) - Method in class distributions.CDF_nct_Amos
 
f_to_integrate(double) - Method in interface quadrature.Gaus8_fcn
 
f_to_integrate(double) - Method in class quadrature.Gaus8Test
 
f_to_minimize(double) - Method in interface optimization.Fmin_methods
 
f_to_minimize(double) - Method in class optimization.FminTest
 
f_to_minimize(double[]) - Method in interface optimization.Uncmin_methods
 
f_to_minimize(double[]) - Method in class optimization.UncminTest_f77
 
f_to_zero(double) - Method in class distributions.CDF_nct_Amos
 
f_to_zero(double) - Method in interface optimization.Fzero_methods
 
f_to_zero(double) - Method in class optimization.FzeroTest
 
factorPosDef(double[][], int) - Method in class linear_algebra.Cholesky
This method factors the n by n symmetric positive definite matrix A as RR´ where R is a lower triangular matrix.
fcn(int, int, double[], double[], double[][], int[]) - Method in interface optimization.Lmder_fcn
 
fcn(int, int, double[], double[], double[][], int[]) - Method in class optimization.LmderTest_f77
 
fcn(int, int, double[], double[], int[]) - Method in interface optimization.Lmdif_fcn
 
fcn(int, int, double[], double[], int[]) - Method in class optimization.LmdifTest_f77
 
fdjac2_f77(Lmdif_fcn, int, int, double[], double[], double[][], int[], double, double[]) - Static method in class optimization.Minpack_f77
The fdjac2 method computes a forward-difference approximation to the m by n Jacobian matrix associated with a specified problem of m functions in n variables.
fit(double[], double[], int, Regress) - Method in class regression.Regress
This method performs a simple linear regression (y = a + b*x).
fm - Variable in class SPV_graphics.SPVGraph
 
Fmin - class optimization.Fmin.
This class was translated by a statistician from the FORTRAN version of fmin.
Fmin_methods - interface optimization.Fmin_methods.
 
Fmin() - Constructor for class optimization.Fmin
 
fmin(double, double, Fmin_methods, double) - Static method in class optimization.Fmin
This method performs a 1-dimensional minimization.
FminTest - class optimization.FminTest.
This class tests the Fmin class.
fnct_inv(double, double, double) - Static method in class distributions.CDF_nct_Amos
This method calculates the inverse of the noncentral T cumulative distribution function.
fnct(double, double, double) - Static method in class distributions.CDF_nct_Amos
This method calculates the noncentral T cumulative distribution function.
fnorm(double, int, int[]) - Static method in class distributions.CDF_Normal_Amos
This method calculates the normal cumulative distribution function.
form(char) - Method in class corejava.Format
Formats a character into a string (like sprintf in C)
form(double) - Method in class corejava.Format
Formats a double into a string (like sprintf in C)
form(long) - Method in class corejava.Format
Formats a long integer into a string (like sprintf in C)
form(String) - Method in class corejava.Format
Formats a string into a larger string (like sprintf in C)
Format - class corejava.Format.
 
Format(String) - Constructor for class corejava.Format
Formats the number following printf conventions.
forslv_f77(int, double[][], double[], double[]) - Static method in class optimization.Uncmin_f77
The forslv_f77 method solves Ax = b where A is a lower triangular matrix.
fstocd_f77(int, double[], Uncmin_methods, double[], double, double[]) - Static method in class optimization.Uncmin_f77
The fstocd_f77 method finds a central difference approximation to the gradient of the function to be minimized.
fstofd_f77(int, double[], Uncmin_methods, double[], double[][], double[], double, double[]) - Static method in class optimization.Uncmin_f77
This version of the fstofd_f77 method finds a finite difference approximation to the Hessian.
fstofd_f77(int, double[], Uncmin_methods, double[], double[], double[], double) - Static method in class optimization.Uncmin_f77
This version of the fstofd_f77 method finds first order finite difference approximations for gradients.
Fzero - class optimization.Fzero.
This class was translated by a statistician from the FORTRAN version of dfzero.
Fzero_methods - interface optimization.Fzero_methods.
 
Fzero() - Constructor for class optimization.Fzero
 
fzero(Fzero_methods, double[], double[], double, double, double, int[]) - Static method in class optimization.Fzero
This method searches for a zero of a function f(x) between the given values b and c until the width of the interval (b,c) has collapsed to within a tolerance specified by the stopping criterion, Math.abs(b-c) <= 2.0*(rw*Math.abs(b)+ae).
FzeroTest - class optimization.FzeroTest.
This class tests the Fzero class.

G

g - Variable in class SPV_graphics.SPVGraph
 
Gaus8 - class quadrature.Gaus8.
This class contains a Java translation of a public domain FORTRAN routine, dgaus8, written by R.
Gaus8_fcn - interface quadrature.Gaus8_fcn.
 
Gaus8() - Constructor for class quadrature.Gaus8
 
gaus8(Gaus8_fcn, double, double, double[], int[]) - Static method in class quadrature.Gaus8
This method integrates real functions of one variable over finite intervals using an adaptive 8-point Legendre-Gauss algorithm.
Gaus8Test - class quadrature.Gaus8Test.
This class tests the Gaus8 class.
generate(double[], int, double[], double[]) - Method in class tests_of_fit.ECDF
This method takes a set of sorted data and returns the associated x,y plotting positions for an empirical cumulative distribution function.
generate(double[], int, int, int, Histo) - Method in class tests_of_fit.Histo
generate(double[], int, NPP) - Method in class tests_of_fit.NPP
This method takes a set of sorted data and returns the associated normal scores (Weisberg-Bingham versions) and the value of the Weisberg-Bingham version of the Shapiro-Wilk statistic for this data.
generate(double[], W2Fit, int, W2PP) - Method in class tests_of_fit.W2PP
This method takes a set of sorted data and returns the associated 2-parameter Weibull scores (Filliben version) and the value of the Filliben version of the correlation statistic for this data.
generate(double[], W3Fit, int, W3PP) - Method in class tests_of_fit.W3PP
This method takes a set of sorted data and returns the associated 3-parameter Weibull scores (Filliben version) and the value of the Filliben version of the correlation statistic for this data.
getAnchor() - Method in class rubberband.Rubberband
 
getEnd() - Method in class rubberband.Rubberband
 
getLast() - Method in class rubberband.Rubberband
 
getStretched() - Method in class rubberband.Rubberband
 
gradient(double[], double[]) - Method in interface optimization.Uncmin_methods
 
gradient(double[], double[]) - Method in class optimization.UncminTest_f77
 
grdchk_f77(int, double[], Uncmin_methods, double[], double[], double[], double[], double[], double, double, double[]) - Static method in class optimization.Uncmin_f77
The grdchk_f77 method checks the analytic gradient supplied by the user.

H

heschk_f77(int, double[], Uncmin_methods, double[], double[], double[][], double[], double[], double, double, int[], double[], double[], double[]) - Static method in class optimization.Uncmin_f77
The heschk_f77 method checks the analytic Hessian supplied by the user.
hessian(double[], double[][]) - Method in interface optimization.Uncmin_methods
 
hessian(double[], double[][]) - Method in class optimization.UncminTest_f77
 
Histo - class tests_of_fit.Histo.
This class provides the x,y pairs needed by a graphics routine to produce a histogram.
Histo() - Constructor for class tests_of_fit.Histo
 
hookdr_f77(int, double[], double[], double[], double[][], double[], double[], double[], double[], Uncmin_methods, double[], double[], double[], double[], int[], boolean[], double[], double[], double[], double[], double[], double[], double[], double, int[]) - Static method in class optimization.Uncmin_f77
The hookdr_f77 method finds a next Newton iterate (xpls) by the More-Hebdon technique.
hookst_f77(int, double[], double[][], double[], double[], double[], double, double[], double[], double[], double[], double[], boolean[], double[], boolean[], double[], double) - Static method in class optimization.Uncmin_f77
The hookst_f77 method finds a new step by the More-Hebdon algorithm.
hsnint_f77(int, double[][], double[], int[]) - Static method in class optimization.Uncmin_f77
The hsnint_f77 method provides the initial Hessian when secant updates are being used.

I

ifail - Variable in class tests_of_fit.Histo
 
imnmx - Variable in class SPV_graphics.SPVGraph
 
info - Variable in class linear_algebra.SVDCException
 
info - Variable in class linear_algebra.NotPosDefException
 
info - Variable in class linear_algebra.NotFullRankException
 
initds(double[], int, double) - Static method in class distributions.Derf
This method determines the number of terms needed in an orthogonal polynomial series so that it meets a specified accuracy.
initpt_f77(int, double[], int, double) - Static method in class optimization.LmdifTest_f77
 
initpt_f77(int, double[], int, double) - Static method in class optimization.LmderTest_f77
 
invertLower(double[][], int) - Method in class linear_algebra.Triangular
This method obtains the inverse of a lower triangular n by n matrix L.
invertPosDef(double[][], int, boolean) - Method in class linear_algebra.Cholesky
This method obtains the inverse of an n by n symmetric positive definite matrix A.

On entrance: If factored == false, the lower triangle of a[ ][ ] should contain the lower triangle of A.
If factored == true, the lower triangle of a[ ][ ] should contain a lower triangular matrix R such that RR´ = A.
invertUpper(double[][], int) - Method in class linear_algebra.Triangular
This method obtains the inverse of an upper triangular n by n matrix U.
isamax_f77(int, double[], int) - Static method in class linear_algebra.Blas_f77
This method finds the index of the element of a vector that has the maximum absolute value.
isamax_j(int, double[], int) - Static method in class linear_algebra.Blas_j
This method finds the index of the element of a vector that has the maximum absolute value.
isort(int[], int[], int[], int) - Static method in class linear_algebra.QRTest_j
 

L

labx - Variable in class SPV_graphics.SPVGraph
 
laby - Variable in class SPV_graphics.SPVGraph
 
last - Variable in class rubberband.Rubberband
 
lastBounds() - Method in class rubberband.Rubberband
 
line - Variable in class SPV_graphics.SPVGraph
 
linear_algebra - package linear_algebra
 
lltslv_f77(int, double[][], double[], double[]) - Static method in class optimization.Uncmin_f77
The lltslv_f77 method solves Ax = b where A has the form L(L transpose) but only the lower triangular part, L, is stored.
lmder_f77(Lmder_fcn, int, int, double[], double[], double[][], double, double, double, int, double[], int, double, int, int[], int[], int[], int[], double[]) - Static method in class optimization.Minpack_f77
The lmder_f77 method minimizes the sum of the squares of m nonlinear functions in n variables by a modification of the Levenberg-Marquardt algorithm.
Lmder_fcn - interface optimization.Lmder_fcn.
 
lmder1_f77(Lmder_fcn, int, int, double[], double[], double[][], double, int[], int[]) - Static method in class optimization.Minpack_f77
The lmder1_f77 method minimizes the sum of the squares of m nonlinear functions in n variables by a modification of the Levenberg-Marquardt algorithm.
LmderTest_f77 - class optimization.LmderTest_f77.
This class tests the Minpack_f77.lmder1_f77 method, a Java translation of the MINPACK lmder1 subroutine.
LmderTest_f77() - Constructor for class optimization.LmderTest_f77
 
lmdif_f77(Lmdif_fcn, int, int, double[], double[], double, double, double, int, double, double[], int, double, int, int[], int[], double[][], int[], double[]) - Static method in class optimization.Minpack_f77
The lmdif_f77 method minimizes the sum of the squares of m nonlinear functions in n variables by a modification of the Levenberg-Marquardt algorithm.
Lmdif_fcn - interface optimization.Lmdif_fcn.
 
lmdif1_f77(Lmdif_fcn, int, int, double[], double[], double, int[]) - Static method in class optimization.Minpack_f77
The lmdif1_f77 method minimizes the sum of the squares of m nonlinear functions in n variables by a modification of the Levenberg-Marquardt algorithm.
LmdifTest_f77 - class optimization.LmdifTest_f77.
This class tests the Minpack_f77.lmdif1_f77 method, a Java translation of the MINPACK lmdif1 subroutine.
LmdifTest_f77() - Constructor for class optimization.LmdifTest_f77
 
lmpar_f77(int, double[][], int[], double[], double[], double, double[], double[], double[], double[], double[]) - Static method in class optimization.Minpack_f77
Given an m by n matrix A, an n by n nonsingular diagonal matrix D, an m-vector b, and a positive number delta, the problem is to determine a value for the parameter par such that if x solves the system
lnsrch_f77(int, double[], double[], double[], double[], double[], double[], Uncmin_methods, boolean[], int[], double[], double[], double[]) - Static method in class optimization.Uncmin_f77
The lnsrch_f77 method finds a next Newton iterate by line search.
LU_f77 - class linear_algebra.LU_f77.
This class contains the LINPACK DGEFA (LU factorization), DGESL (solve), and DGEDI (determinant and inverse) routines.
LU_f77() - Constructor for class linear_algebra.LU_f77
 
LU_j - class linear_algebra.LU_j.
This class contains the LINPACK DGEFA (LU factorization), DGESL (solve), and DGEDI (determinant and inverse) routines.
LU_j() - Constructor for class linear_algebra.LU_j
 
LUTest_f77 - class linear_algebra.LUTest_f77.
This class tests the LU_f77 methods.
LUTest_f77() - Constructor for class linear_algebra.LUTest_f77
 
LUTest_j - class linear_algebra.LUTest_j.
This class tests the LU_j methods.
LUTest_j() - Constructor for class linear_algebra.LUTest_j
 

M

main(String[]) - Static method in class corejava.Format
a test stub for the format class
main(String[]) - Static method in class distributions.CDF_Weibull3_Test
 
main(String[]) - Static method in class distributions.CDF_Weibull2_Test
 
main(String[]) - Static method in class distributions.CDF_Normal_Test
 
main(String[]) - Static method in class distributions.Nct_invTest
 
main(String[]) - Static method in class distributions.NctTest
 
main(String[]) - Static method in class distributions.DerfTest
 
main(String[]) - Static method in class distributions.CDF_Normal_Amos_Test
 
main(String[]) - Static method in class linear_algebra.SVDCTest_j
 
main(String[]) - Static method in class linear_algebra.SVDCTest_f77
 
main(String[]) - Static method in class linear_algebra.QRTest_j
 
main(String[]) - Static method in class linear_algebra.QRTest_f77
 
main(String[]) - Static method in class linear_algebra.LUTest_j
 
main(String[]) - Static method in class linear_algebra.LUTest_f77
 
main(String[]) - Static method in class linear_algebra.CholTest_j
 
main(String[]) - Static method in class linear_algebra.CholTest_f77
 
main(String[]) - Static method in class linear_algebra.CholTest
 
main(String[]) - Static method in class optimization.UncminTest_f77
 
main(String[]) - Static method in class optimization.LmdifTest_f77
 
main(String[]) - Static method in class optimization.LmderTest_f77
 
main(String[]) - Static method in class optimization.FzeroTest
 
main(String[]) - Static method in class optimization.FminTest
 
main(String[]) - Static method in class quadrature.Gaus8Test
 
marker - Variable in class SPV_graphics.SPVGraph
 
markersize - Variable in class SPV_graphics.SPVGraph
 
markertype - Variable in class SPV_graphics.SPVGraph
 
matmat_f77(double[][], double[][], double[][], int, int, int) - Static method in class linear_algebra.Blas_f77
This method multiplies an n x p matrix by a p x r matrix.
matmat_j(double[][], double[][], double[][], int, int, int) - Static method in class linear_algebra.Blas_j
This method multiplies an n x p matrix by a p x r matrix.
mattran_f77(double[][], double[][], int, int) - Static method in class linear_algebra.Blas_f77
This method obtains the transpose of an n x p matrix.
mattran_j(double[][], double[][], int, int) - Static method in class linear_algebra.Blas_j
This method obtains the transpose of an n x p matrix.
matvec_f77(double[][], double[], double[], int, int) - Static method in class linear_algebra.Blas_f77
This method multiplies an n x p matrix by a p x 1 vector.
matvec_j(double[][], double[], double[], int, int) - Static method in class linear_algebra.Blas_j
This method multiplies an n x p matrix by a p x 1 vector.
Minpack_f77 - class optimization.Minpack_f77.
This class contains Java translations of the MINPACK nonlinear least squares routines.
Minpack_f77() - Constructor for class optimization.Minpack_f77
 
mvmltl_f77(int, double[][], double[], double[]) - Static method in class optimization.Uncmin_f77
The mvmltl_f77 method computes y = Lx where L is a lower triangular matrix stored in A.
mvmlts_f77(int, double[][], double[], double[]) - Static method in class optimization.Uncmin_f77
The mvmlts_f77 method computes y = Ax where A is a symmetric matrix stored in its lower triangular part.
mvmltu_f77(int, double[][], double[], double[]) - Static method in class optimization.Uncmin_f77
The mvmltu_f77 method computes Y = (L transpose)X where L is a lower triangular matrix stored in A (L transpose is taken implicitly).

N

n - Variable in class SPV_graphics.SPVGraph
 
n - Variable in class regression.Regress
 
Nct_invTest - class distributions.Nct_invTest.
This class tests the noncentral t cdf inverse in CDF_nct_Amos.
Nct_invTest() - Constructor for class distributions.Nct_invTest
 
NctTest - class distributions.NctTest.
This class tests the noncentral t cdf in CDF_nct_Amos.
NctTest() - Constructor for class distributions.NctTest
 
Normal - class rannum.Normal.
This class contains a Java version of the FORTRAN routine rnor which generates standard normal random numbers.
Normal(int) - Constructor for class rannum.Normal
 
normi(double) - Static method in class linear_algebra.SVDCTest_j
This is a normal cdf inverse routine.
normi(double) - Static method in class linear_algebra.SVDCTest_f77
This is a normal cdf inverse routine.
normi(double) - Static method in class linear_algebra.QRTest_j
This is a normal cdf inverse routine.
normi(double) - Static method in class linear_algebra.QRTest_f77
This is a normal cdf inverse routine.
normp(double) - Static method in class distributions.CDF_Normal
This method calculates the normal cumulative distribution function.
NotFullRankException - exception linear_algebra.NotFullRankException.
This is the exception produced by a Triangular method if a matrix has at least one zero diagonal element.
NotFullRankException() - Constructor for class linear_algebra.NotFullRankException
 
NotFullRankException(int) - Constructor for class linear_algebra.NotFullRankException
 
NotFullRankException(String) - Constructor for class linear_algebra.NotFullRankException
 
NotPosDefException - exception linear_algebra.NotPosDefException.
This is the exception produced by the Cholesky factorization if it determines that the matrix to be factored is not positive definite.
NotPosDefException() - Constructor for class linear_algebra.NotPosDefException
 
NotPosDefException(int) - Constructor for class linear_algebra.NotPosDefException
 
NotPosDefException(String) - Constructor for class linear_algebra.NotPosDefException
 
NPP - class tests_of_fit.NPP.
This class returns the appropriate Weisberg-Bingham scores as well as the Weisberg-Bingham version of the Shapiro-Wilk test of normality statistic.
NPP() - Constructor for class tests_of_fit.NPP
 
npts - Variable in class tests_of_fit.Histo
 

O

optchk_f77(int, double[], double[], double[], double[], double[], int[], int[], double, double[], int[], int[], int[], int[], double[], int[]) - Static method in class optimization.Uncmin_f77
The optchk_f77 method checks the input for reasonableness.
optdrv_f77(int, double[], Uncmin_methods, double[], double[], int[], int[], int[], int[], int[], int[], int[], double[], double[], double[], double[], double[], double[], double[], int[], double[][], double[], double[], double[], double[], double[], double[], double[], double[]) - Static method in class optimization.Uncmin_f77
The optdrv_f77 method is the driver for the nonlinear optimization problem.
optif0_f77(int, double[], Uncmin_methods, double[], double[], double[], int[], double[][], double[]) - Static method in class optimization.Uncmin_f77
The optif0_f77 method minimizes a smooth nonlinear function of n variables.
optif9_f77(int, double[], Uncmin_methods, double[], double[], int[], int[], int[], int[], int[], int[], int[], double[], double[], double[], double[], double[], double[], double[], int[], double[][], double[]) - Static method in class optimization.Uncmin_f77
The optif9_f77 method minimizes a smooth nonlinear function of n variables.
optimization - package optimization
 
optstp_f77(int, double[], double[], double[], double[], int[], int[], int[], double[], double[], double[], double[], int[], int[], boolean[], int[]) - Static method in class optimization.Uncmin_f77
The optstp_f77 method determines whether the algorithm should terminate due to any of the following: 1) problem solved within user tolerance 2) convergence within user tolerance 3) iteration limit reached 4) divergence or too restrictive maximum step (stepmx) suspected Translated by Steve Verrill, May 12, 1998.

P

ph2wh(int) - Method in class SPV_graphics.SPVGrint
pixel height to world coordinate height
pred - Variable in class regression.Regress
 
print(PrintStream, String, char) - Static method in class corejava.Format
prints a formatted number following printf conventions
print(PrintStream, String, double) - Static method in class corejava.Format
prints a formatted number following printf conventions
print(PrintStream, String, long) - Static method in class corejava.Format
prints a formatted number following printf conventions
print(PrintStream, String, String) - Static method in class corejava.Format
prints a formatted number following printf conventions
printPrompt(String) - Static method in class corejava.Console
print a prompt on the console but don't print a newline
pw2ww(int) - Method in class SPV_graphics.SPVGrint
pixel width to world coordinate width

Q

QR_f77 - class linear_algebra.QR_f77.
This class contains the LINPACK DQRDC (QR decomposition) and DQRSL (QR solve) routines.
QR_f77() - Constructor for class linear_algebra.QR_f77
 
QR_j - class linear_algebra.QR_j.
This class contains the LINPACK DQRDC (QR decomposition) and DQRSL (QR solve) routines.
QR_j() - Constructor for class linear_algebra.QR_j
 
qraux1_f77(int, double[][], int) - Static method in class optimization.Uncmin_f77
The qraux1_f77 method interchanges rows i,i+1 of the upper Hessenberg matrix r, columns i to n.
qraux2_f77(int, double[][], int, double, double) - Static method in class optimization.Uncmin_f77
The qraux2_f77 method pre-multiplies r by the Jacobi rotation j(i,i+1,a,b).
qrfac_f77(int, int, double[][], boolean, int[], double[], double[], double[]) - Static method in class optimization.Minpack_f77
The qrfac_f77 method uses Householder transformations with column pivoting (optional) to compute a QR factorization of the m by n matrix A.
qrsolv_f77(int, double[][], int[], double[], double[], double[], double[], double[]) - Static method in class optimization.Minpack_f77
Given an m by n matrix A, an n by n diagonal matrix D, and an m-vector b, the problem is to determine an x which solves the system
QRTest_f77 - class linear_algebra.QRTest_f77.
This class tests the (LINPACK) QR classes.
QRTest_f77() - Constructor for class linear_algebra.QRTest_f77
 
QRTest_j - class linear_algebra.QRTest_j.
This class tests the (LINPACK) QR classes.
QRTest_j() - Constructor for class linear_algebra.QRTest_j
 
qrupdt_f77(int, double[][], double[], double[]) - Static method in class optimization.Uncmin_f77
The qrupdt_f77 method finds an orthogonal n by n matrix, Q*, and an upper triangular n by n matrix, R*, such that (Q*)(R*) = R+U(V+).
quadrature - package quadrature
 

R

r - Variable in class tests_of_fit.W3PP
 
r - Variable in class tests_of_fit.W2PP
 
rannum - package rannum
 
readDouble(String) - Static method in class corejava.Console
read a floating point number from the console.
readInt(String) - Static method in class corejava.Console
read an integer from the console.
readString() - Static method in class corejava.Console
read a string from the console.
readString(String) - Static method in class corejava.Console
read a string from the console.
readWord() - Static method in class corejava.Console
read a word from the console.
Real_Sorts - class sorts.Real_Sorts.
This class permits one to perform sorts of real numbers.
Real_Sorts_f77 - class sorts.Real_Sorts_f77.
This class permits one to perform sorts of real numbers.
Real_Sorts_f77() - Constructor for class sorts.Real_Sorts_f77
 
Real_Sorts() - Constructor for class sorts.Real_Sorts
 
Regress - class regression.Regress.
This class performs simple regressions (y = a + b*x).
Regress() - Constructor for class regression.Regress
 
regression - package regression
 
resid - Variable in class regression.Regress
 
result_f77(int, double[], double[], double[], double[][], double[], int[], int) - Static method in class optimization.Uncmin_f77
The result_f77 method prints information.
rnor() - Method in class rannum.Normal
 
rsort(double[], double[], int[], int) - Static method in class sorts.Real_Sorts_f77
This method attempts to perform an n*log(n) sort rather than an n*n sort.
rsort(double[], double[], int[], int) - Static method in class sorts.Real_Sorts
This method attempts to perform an n*log(n) sort rather than an n*n sort.
rubberband - package rubberband
 
Rubberband - class rubberband.Rubberband.
A abstract base class for rubberbands.
Rubberband(Component) - Constructor for class rubberband.Rubberband
 
RubberbandRectangle - class rubberband.RubberbandRectangle.
A Rubberband that does rectangles.
RubberbandRectangle(Component) - Constructor for class rubberband.RubberbandRectangle
 
RubberbandRectangleX - class rubberband.RubberbandRectangleX.
A Rubberband that does "crossed-out" rectangles
RubberbandRectangleX(Component) - Constructor for class rubberband.RubberbandRectangleX
 

S

sclmul_f77(int, double, double[], double[]) - Static method in class optimization.Uncmin_f77
The sclmul_f77 method multiplies a vector by a scalar.
scores - Variable in class tests_of_fit.W3PP
 
scores - Variable in class tests_of_fit.W2PP
 
scores - Variable in class tests_of_fit.NPP
 
secfac_f77(int, double[], double[], double[][], double[], double[], double, int[], double, int[], boolean[], double[], double[], double[], double[]) - Static method in class optimization.Uncmin_f77
The secfac_f77 method updates the Hessian by the BFGS factored technique.
secunf_f77(int, double[], double[], double[][], double[], double[], double[], double, int[], double, int[], boolean[], double[], double[], double[]) - Static method in class optimization.Uncmin_f77
The secunf_f77 method updates the Hessian by the BFGS unfactored approach.
setdiff(double, double) - Method in class SPV_graphics.SPVGrint
This method sets the width and height of the world coordinate system.
setMarkerSize(double) - Method in class SPV_graphics.SPVGrint
setdiff must be called before setMarkerSize.
setmin(double, double) - Method in class SPV_graphics.SPVGrint
This method sets the minimum x and y values for the world coordinate system.
sign_f77(double, double) - Static method in class linear_algebra.Blas_f77
This method implements the FORTRAN sign (not sin) function.
sign_j(double, double) - Static method in class linear_algebra.Blas_j
This method implements the FORTRAN sign (not sin) function.
sign(double, double) - Static method in class distributions.Derf
This method implements the FORTRAN sign (not sin) function.
sign(double, double) - Static method in class quadrature.Gaus8
This method implements the FORTRAN sign (not sin) function.
sndofd_f77(int, double[], Uncmin_methods, double[], double[][], double[], double, double[], double[]) - Static method in class optimization.Uncmin_f77
The sndofd_f77 method finds second order forward finite difference approximations to the Hessian.
solveLower(double[][], double[], double[], int) - Method in class linear_algebra.Triangular
This method obtains the solution, y, of the equation Ly = b where L is a known full rank lower triangular n by n matrix, and b is a known vector of length n.
solvePosDef(double[][], double[], double[], int, boolean) - Method in class linear_algebra.Cholesky
This method solves the equation
solveUpper(double[][], double[], double[], int) - Method in class linear_algebra.Triangular
This method obtains the solution, x, of the equation Ux = y where U is a known full rank upper triangular n by n matrix, and y is a known vector of length n.
sorted_resid - Variable in class regression.Regress
 
sorts - package sorts
 
SPV_graphics - package SPV_graphics
 
spvDrawLine(Graphics, double, double, double, double) - Method in class SPV_graphics.SPVGrint
DrawLine that uses world coordinates rather than pixel coordinates.
SPVGraph - class SPV_graphics.SPVGraph.
This class contains the main graphics routine.
SPVGraph() - Constructor for class SPV_graphics.SPVGraph
 
spvGraph(SPVGrint, SPVGraph) - Method in class SPV_graphics.SPVGraph
 
SPVGrint - class SPV_graphics.SPVGrint.
This class initializes the graphics process.
SPVGrint(int, int) - Constructor for class SPV_graphics.SPVGrint
 
ssqfcn_f77(int, int, double[], double[], int) - Static method in class optimization.LmdifTest_f77
 
ssqfcn_f77(int, int, double[], double[], int) - Static method in class optimization.LmderTest_f77
 
ssqjac_f77(int, int, double[], double[][], int) - Static method in class optimization.LmderTest_f77
 
stretch(Point) - Method in class rubberband.Rubberband
 
stretched - Variable in class rubberband.Rubberband
 
SVDC_f77 - class linear_algebra.SVDC_f77.
This class contains the LINPACK DSVDC (singular value decomposition) routine.
SVDC_f77() - Constructor for class linear_algebra.SVDC_f77
 
SVDC_j - class linear_algebra.SVDC_j.
This class contains the LINPACK DSVDC (singular value decomposition) routine.
SVDC_j() - Constructor for class linear_algebra.SVDC_j
 
SVDCException - exception linear_algebra.SVDCException.
This is the exception produced by the Singular Value Decomposition method.
SVDCException() - Constructor for class linear_algebra.SVDCException
 
SVDCException(int) - Constructor for class linear_algebra.SVDCException
 
SVDCException(String) - Constructor for class linear_algebra.SVDCException
 
SVDCTest_f77 - class linear_algebra.SVDCTest_f77.
This class tests the (LINPACK) SVDC method.
SVDCTest_f77() - Constructor for class linear_algebra.SVDCTest_f77
 
SVDCTest_j - class linear_algebra.SVDCTest_j.
This class tests the (LINPACK) SVDC method.
SVDCTest_j() - Constructor for class linear_algebra.SVDCTest_j
 
sw - Variable in class tests_of_fit.NPP
 
SW(double[], double[], int) - Method in class tests_of_fit.NPP
This routine calculates the value of a version of the Shapiro-Wilk test of normality statistic.

T

tests_of_fit - package tests_of_fit
 
tha(double, double, double[], double[]) - Static method in class distributions.CDF_nct_Amos
This method calculates the t(h,a) integral of Owen.
TicDraw - class SPV_graphics.TicDraw.
This class draws x and y axis tics and labels.
TicDraw() - Constructor for class SPV_graphics.TicDraw
 
TicID - class SPV_graphics.TicID.
This class determines the x and y axis tic locations and labels.
TicID() - Constructor for class SPV_graphics.TicID
 
title - Variable in class SPV_graphics.SPVGraph
 
tregup_f77(int, double[], double[], double[], double[][], Uncmin_methods, double[], double[], boolean[], double[], double[], double[], int[], double[], double[], double[], double[], boolean[], int, double[]) - Static method in class optimization.Uncmin_f77
The tregup_f77 method decides whether to accept xpls = x + sc as the next iterate and update the trust region dlt.
Triangular - class linear_algebra.Triangular.
This class contains: methods to solve Ly = b and Ux = y where L is a full rank lower triangular matrix and U is a full rank upper triangular matrix.
Triangular() - Constructor for class linear_algebra.Triangular
 

U

Uncmin_f77 - class optimization.Uncmin_f77.
This class contains Java translations of the UNCMIN unconstrained optimization routines.
Uncmin_f77() - Constructor for class optimization.Uncmin_f77
 
Uncmin_methods - interface optimization.Uncmin_methods.
 
UncminTest_f77 - class optimization.UncminTest_f77.
This class tests the Uncmin_f77 class.
uni() - Method in class rannum.Uniform
 
Uniform - class rannum.Uniform.
This class contains a Java version of the FORTRAN routine uni which generates uniform(0,1) random numbers.
Uniform(int) - Constructor for class rannum.Uniform
 

W

w2cdf(double, double, double) - Static method in class distributions.CDF_Weibull2
This method calculates the 2-parameter Weibull cumulative distribution function.
W2Fit - class tests_of_fit.W2Fit.
This object contains the results from a fit of a 2-parameter Weibull distribution to a set of data.
W2Fit(double, double) - Constructor for class tests_of_fit.W2Fit
 
w2inv(double, double, double) - Static method in class distributions.CDF_Weibull2
This method calculates the inverse of the 2-parameter Weibull cumulative distribution function.
W2PP - class tests_of_fit.W2PP.
This class returns appropriate scores as well as a correlation test of fit value.
W2PP() - Constructor for class tests_of_fit.W2PP
 
w3cdf(double, double, double, double) - Static method in class distributions.CDF_Weibull3
This method calculates the 3-parameter Weibull cumulative distribution function.
W3Fit - class tests_of_fit.W3Fit.
This object contains the results from a fit of a 3-parameter Weibull distribution to a set of data.
W3Fit(double, double, double) - Constructor for class tests_of_fit.W3Fit
 
w3inv(double, double, double, double) - Static method in class distributions.CDF_Weibull3
This method calculates the inverse of the 3-parameter Weibull cumulative distribution function.
W3PP - class tests_of_fit.W3PP.
This class returns appropriate scores as well as a correlation test of fit value.
W3PP() - Constructor for class tests_of_fit.W3PP
 
wh2ph(double) - Method in class SPV_graphics.SPVGrint
world height to pixel height
ww2pw(double) - Method in class SPV_graphics.SPVGrint
world width to pixel width

X

x - Variable in class SPV_graphics.SPVGraph
 
x - Variable in class regression.Regress
 
xhigh - Variable in class SPV_graphics.SPVGraph
 
xlow - Variable in class SPV_graphics.SPVGraph
 
xmax - Variable in class SPV_graphics.SPVGraph
 
xmax - Variable in class tests_of_fit.Histo
 
xmin - Variable in class SPV_graphics.SPVGraph
 
xmin - Variable in class tests_of_fit.Histo
 
xnormi(double) - Static method in class distributions.CDF_Normal
This method calculates the normal cdf inverse function.
xp2xw(int) - Method in class SPV_graphics.SPVGrint
x pixel coordinates to world coordinates
xpl - Variable in class tests_of_fit.Histo
 
xw2xp(double) - Method in class SPV_graphics.SPVGrint
x world coordinates to pixel coordinates

Y

y - Variable in class SPV_graphics.SPVGraph
 
yhigh - Variable in class SPV_graphics.SPVGraph
 
ylow - Variable in class SPV_graphics.SPVGraph
 
ymax - Variable in class SPV_graphics.SPVGraph
 
ymax - Variable in class tests_of_fit.Histo
 
ymin - Variable in class SPV_graphics.SPVGraph
 
ymin - Variable in class tests_of_fit.Histo
 
yp2yw(int) - Method in class SPV_graphics.SPVGrint
y pixel coordinates to world coordinates
ypl - Variable in class tests_of_fit.Histo
 
yw2yp(double) - Method in class SPV_graphics.SPVGrint
y world coordinates to pixel coordinates

A B C D E F G H I L M N O P Q R S T U W X Y