robeth

Diagonal matrix D for the binomial case in discrete GLM

Parametric estimate of survival cdf

Auxiliary function to find mu and sigma parameter for extended loggamma distribution

Auxiliary function to find lambda parameter for extended loggamma distribution

Auxiliary function to compute quantiles of survival cdf

Uniform random number generator

Auxiliary function for the computation of QQopt

Auxiliary function for the computation of QQopt

Adds a column vector to a transformed design matrix and updates its QR-decomposition

Asymptotic relative efficiency of a general M-estimate for a model with mu quantitative covariates with or without a constant term

Asymptotic relative efficiency of a general M-estimate for a model with mu quantitative and nu qualitative covariates

Binomial probability distribution

Complemented error function (single precision)

Complemented error function (double precision)

Computation of fC.fC.inv(AT A) for a given matrix A and scale factor fC

Chi weight function for location and regression

Chi weight function for location and regression

Cumulative Chi-square distribution function

Determination of the parameters a2 and b2 of the Huber weight function from the proportion eps of contamination

Determination of the parameter d of the Huber weight function

Determination of the parameter c of the Huber weight function from the proportion eps of contamination

Determination of the correction factor for the M-estimate based on Huber weight function

Initial values for the iterative algorithms implemented in CYFALG, CYNALG, and CYGALG

Initial values for the Rocke estimates of covariance

Gives the current values ofthe parameters of the ROBETH subroutine common blocks

Inverse of the cumulative Chi2-distribution function

Fixed-point algorithm for the computation of an M-estimate of multivariate location and scatter

Conjugate gradient algorithm for the computation of an M-estimate of multivariate location and scatter

Newton-type algorithm for the computation of an M-estimate of multivariate location and scatter

Assigns values to the ROBETH parameters included in common blocks

Sets default parameters for regression estimates

Provide default values for most scalar parameters used by the Robeth subroutines

Forms the scalar (dot) product of two vectors

Forms the scalar (dot) product of two vectors (double precision)

Diagonal matrix D for the Poisson case in discrete GLM

Exchanges two columns of a symmetric matrix

Exchanges two columns of a symmetric matrix (double precision)

Cumulative F-distribution function

Determination of the j-th order statistic

Cumulative Gaussian distribution function

Cumulative Gaussian distribution function (double precision)

Diagonal matrices D_G and E_G

Initial values of theta, A and c_i,...,c_n

The total deviance of the fitted generalizrd linear model

Fixed-point algorithm for the A-step

Newton-type algorithm for the c-step

Main algorithm

Newton-type algorithm for the theta-step

Constructs and/or applies a single elementary Householder transformation

Constructs and/or applies a single elementary Householder transformation (double precision)

Resampling algorithm for the computation of the LMS estimate

Resampling algorithm for the computation of the LTS estimate

Resampling algorithm for the computation of S-estimates

Resampling algorithm for the computation of weighted S-estimates

Incomplete Gamma-integral function

Backtransformation of the covariance matrix of the coefficient estimates

Diagonal hat matrices D_M, E_M, D_S, and E_S

Diagonal 'check' matrices D_M, E_M, D_S, and E_S

Correction factor f_H for the covariance matrix of a Huber-type estimate

Covariance matrix of the coefficient estimates of the form f.inv(XT X) in the transformed coordinate system

Diagonal matrices D_M, E_M, D_S, E_S when psi is the Huber function

Diagonal matrices D_M, E_M, D_S, E_S when psi is a user-supplied function

Covariance matrix of the coefficient estimates of the form f.inv(XT X)

Covariance matrix of the coefficient estimates of the form f.inv(S1) S2 inv(S1)

Logarithm at the Gamma-function at the point x

Computation of Beta0 = Phi_inv(0.75)

Computation of Int Chi(s) dPhi(s) when Chi=Psi.Psi/2 and Psi is the Huber function

Computation of Int Chi(s) dPhi(s) when Chi is a user-supplied function

Classical estimates of mean and standard deviation

Computation of Int Psi(s).Psi(s) dPhi(s) and Int Psi'(s) dPhi(s) when Psi is the Huber function

Computation of Int Psi(s).Psi(s) dPhi(s) and Int Psi'(s) dPhi(s) when Psi is a user-supplied external function

Inverts the approximate null distribution of the one-sample Wilcoxon test statistic

Inverts the approximate null distribution of the sign test statistic

Inverts the approximate null distribution of the Mann-Whitney test statistic

Median an median absolute deviation

t-test for the shift parameter

Median and median absolute deviation

Computation of Li, li and lip

M-estimate of location with simultaneous estimation of scale

Hodges-Lehman estimate and confidence intervals for the center of symmetry based on the one-sample Wilcoxon test

Nonparametric estimate and confidence intervals for the shift parameter based on the Mann-Whitney test statistic

tau-test for the shift parameter

W-algorithm for M-estimate of location

Cholesky decomposition of a symmetric matrix

Cholesky decomposition of a symmetric matrix (double precision)

Print a message when a required argument is missing

Multiplies a full matrix by a full matrix

Multiplies a full matrix by a full matrix (double precision)

Generation and comparison of all regressions on subsets of covariates

Multiplies a full matrix by a vector

Multiplies a full matrix by a vector (double precision)

Computes the diagonal elements of the hat matrix

Inverts a triangular matrix

Inverts a triangular matrix (double precision)

Computation of (robust) t-statistics for t-directed search

Multiplies a lower-triangular matrix by a vector

Multiplies a lower-triangular matrix by a vector (double precision)

Multiplies a symmetric matrix by a full matrix

Multiplies a symmetric matrix by a full matrix when the result is a symmetric matrix

Multiplies a symmetric matrix by a full matrix when the result is a symmetric matrix

Multiplies a symmetric matrix by a full matrix (double precision)

Multiplies a symmetric matrix by a symmetric matrix

Multiplies a symmetric matrix by a symmetric matrix (double precision)

Multiplies an upper-triangular matrix by its transpose

Multiplies an upper-triangular matrix by its transpose (double precision)

Multiplies a lower-triangular matrix by its transpose

Multiplies a lower-triangular matrix by its transpose (double precision)

Multiplies a triangular matrix by a triangular matrix

Multiplies a triangular matrix by a triangular matrix (double precision)

Multiplies an upper-triangular matrix by a vector

Multiplies an upper-triangular matrix by a vector

High breakdown point and high efficiency regression with test for bias

Simultaneous computation of the MVE and LMS estimates

Logarithm of the Gamma-function at the point n/2

Forms the Euclidean norm of a vector

Forms the Euclidean norm of a vector (double precision)

Permutes the columns of a matrix by means of transpositions

Permutes the elements of a vector

Poisson distribution

Algorithmic determination of the smallest double precision positive number x

Algorithmic determination of the smallest double precision positive number x

Cumulative t-distribution function

psi weight function for location and regression

psi weight function for location and regression

psi' weight function for location and regression

psi' weight function for location and regression

Inverse of the standard Gaussian cumulative distribution function

rho weight function for location and regression

Rho weight function for location and regression

Computation of the constant Beta0

Computation of the constant Beta when Chi=Psi.Psi/2 and Psi is the Huber function

Computation of the constant Beta when Chi is a user-supplied function

Solution of the least squares problem

Solution of the least absolute residual problem

Double precision version of RIMTRF

Upper triangularization (QR-decomposition) of the design matrix and determination of its pseudorank

Removes a column from a transformed design matrix and updates its QR-decomposition

Interface for the FORTRAN programs developed at the ETH-Zuerich and then at IUMSP-Lausanne

Cumulative distribution and density function of a linear combination of chi-2 random variables

Bounded influence regression

H-algorithm for M-estimates

Newton algorithm with adaptive steps for M-estimates

S-algorithm for M-estimates

Iterative algorithm for the computation of an M-estimate of the scale parameter when the residuals are given

W-algorithm for M-estimates

Scales a vector by a constant

Scales a double precision vector by a constant

Sorts the components of a vector in ascending order

Sorts the components of a vector in ascending order and permutes the components of another vector accordingly

Interchanges two vectors

Interchanges two vectors (double precision)

Asymptotic relative efficiency of the tau-test

Computes the Rn2-test statistic for a linear hypothesis in canonical form

Computes the tau-test statistic for a linear hypothesis in canonical form

Permutes the columns of the design matrix: Predictors in omega are placed in the first q positions

Convert local variable to Fortran character

Convert local variable to Fortran double precision

Convert local variable to Fortran integer

Convert local variable to Fortran single precision

Inverse of the cumulative t-distribution function

Computes the matrix Ktau

Computes the eigenvalues of the matrix Ktau

u weight function for covariances

u weight function for covariances

ub weight function for M-estimates in GLM

u' weight function for covariances

u' weight function for covariances

Dummy u user function (double precision)

Dummy u user function

v weight function for covariances

v' weight function for covariances

v weight function for covariances

w weight function for covariances

Schweppe original weight proposal

Initial value of the matrix A

w' weight function for covariances

w' weight function for covariances

w weight function

w weight function for covariances

Fixed-point algorithm for the computation of the matrix A

Modified fixed-point algorithm for collinear data in the standardized case

Conjugate gradient algorithm for the computation of the lower-triangular matrix A in the standardized case

Newton-Huber algorithm for the computation of the lower-triangular matrix A in the standardized case

Gaussian density function

Density of the norm of a standard Gaussian vector with p components

Evaluates a quadratic form

Evaluates a quadratic form (double precision)

Zeng method for censored data