Package: RobStatTM 1.0.11

Matias Salibian-Barrera

RobStatTM: Robust Statistics: Theory and Methods

Companion package for the book: "Robust Statistics: Theory and Methods, second edition", <http://www.wiley.com/go/maronna/robust>. This package contains code that implements the robust estimators discussed in the recent second edition of the book above, as well as the scripts reproducing all the examples in the book.

Authors:Matias Salibian-Barrera [cre], Victor Yohai [aut], Ricardo Maronna [aut], Doug Martin [aut], Gregory Brownson [aut], Kjell Konis [aut], Kjell Konis [cph], Christophe Croux [ctb], Gentiane Haesbroeck [ctb], Martin Maechler [cph], Manuel Koller [cph], Matias Salibian-Barrera [aut]

RobStatTM_1.0.11.tar.gz
RobStatTM_1.0.11.zip(r-4.7-x86_64)RobStatTM_1.0.11.zip(r-4.7-arm64)RobStatTM_1.0.11.zip(r-4.6-x86_64)RobStatTM_1.0.11.zip(r-4.6-arm64)
RobStatTM_1.0.11.tar.gz(r-4.7-arm64)RobStatTM_1.0.11.tar.gz(r-4.7-x86_64)RobStatTM_1.0.11.tar.gz(r-4.6-arm64)RobStatTM_1.0.11.tar.gz(r-4.6-x86_64)
RobStatTM_1.0.11.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
RobStatTM/json (API)

# Install 'RobStatTM' in R:
install.packages('RobStatTM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblas

5.16 score 10 packages 12k downloads 1 mentions 46 exports 7 dependencies

Last updated from:1955d4c12b. Checks:9 OK, 1 WARNING. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK292
linux-devel-x86_64OK116
source / vignettesOK173
linux-release-arm64OK89
linux-release-x86_64OK207
windows-devel-arm64OK275
windows-devel-x86_64OK120
windows-release-arm64WARNING206
windows-release-x86_64OK322
wasm-releaseOK103

Exports:bisquareBYlogregcov.dcmlcovClassiccovRobcovRobMMcovRobRockeDCMLfastmvehuberinitPPINVTR2KurtSDNewlmrobdet.controllmrobdetDCMLlmrobdetLinTestlmrobdetMMlmrobdetMM.RFPElmrobMlmrobM.controllocScaleMlogregBYlogregWBYlogregWMLMLocDisMMPYMMultiSHRmoptmoptv0Multirobuoptoptv0pcaRobSprcompRobrefine.smrhorhoprimerhoprime2rob.linear.testRockeMultiscaleMSMPCASMPYstep.lmrobdetMMWBYlogregWMLlogreg

Dependencies:DEoptimRlatticemvtnormpcaPPpyinitrobustbaserrcov

Optimal Bias Robust Regression Psi and Rho
1 Introduction | 2 Optimal Psi and Rho Functions | 3 A Modified Optimal Estimator | 4 MM-Estimator Implementation | A1 The optimalRhoPsi R Package
Rendered fromOptimalBiasRobustRegressionPsiandRho.pdf.asisusingR.rsp::asis

Last update: 2024-10-17
Started: 2023-04-05

Polynomial Opt and mOpt Rho Functions in RobStatTM
Rendered fromPolynomialOptandmOptRhoFunctions.pdf.asisusingR.rsp::asis

Last update: 2024-10-17
Started: 2023-04-05

RobStatTM Package Vignette
1 The RobStatTM Scripts and Data Sets | 2 Convergence of Algorithms for Computing Robust Estimates
Rendered fromVignetteRobStatTM.pdf.asisusingR.rsp::asis

Last update: 2024-10-17
Started: 2020-03-02

Using the fit.models Package with RobStatTM
1 The fit.models Package and Function | 2 Robust Versus Least Squares Fits of Linear Regression Models | 3 Robust versus Classical Covariance Matrices
Rendered fromfitmodelsusingRobStatTM.pdf.asisusingR.rsp::asis

Last update: 2024-10-17
Started: 2021-11-30

Readme and manuals

Help Manual

Help pageTopics
Alcohol dataalcohol
Algae dataalgae
Biochem databiochem
Tuning parameter the rho loss functionsbisquare
Breslow Databreslow.dat
Bus databus
Approximate covariance matrix of the DCML regression estimator.cov.dcml
Classical Covariance EstimationcovClassic
Robust multivariate location and scatter estimatorscovRob Multirobu
MM robust multivariate location and scatter estimatorcovRobMM MMultiSHR
Rocke's robust multivariate location and scatter estimatorcovRobRocke RockeMulti
DCML regression estimatorDCML
RFPE of submodels of an 'lmrobdetMM' fitdrop1.lmrobdetMM
Minimum Volume Ellipsoid covariance estimatorfastmve
Flour dataflour
Glass dataglass
Hearing datahearing
Tuning parameter the rho loss functionshuber
Image dataimage
Robust multivariate location and scatter estimatorsinitPP KurtSDNew
Robust R^2 coefficient of determinationINVTR2
Leukemia Dataleuk.dat
Tuning parameters for lmrobdetMM and lmrobdetDCMLlmrobdet.control
Robust Distance Constrained Maximum Likelihood estimators for linear regressionlmrobdetDCML
Robust likelihood ratio test for linear hypotheseslmrobdetLinTest rob.linear.test
Robust Linear Regression EstimatorslmrobdetMM
Robust Final Prediction ErrorlmrobdetMM.RFPE
Robust estimators for linear regression with fixed designslmrobM
Tuning parameters for lmrobMlmrobM.control
Robust univariate location and scale M-estimatorslocScaleM MLocDis
Bianco and Yohai estimator for logistic regressionBYlogreg logregBY
Bianco and Yohai estimator for logistic regressionlogregWBY WBYlogreg
Weighted likelihood estimator for the logistic modellogregWML WMLlogreg
Mineral datamineral
MM regression estimator using Pen~a-Yohai candidatesMMPY
Tuning parameter for a rho function in the modified (asymptotic bias-) optimal familymopt
Tuning parameter for a rho function in the modified (asymptotic bias-) optimal familymoptv0
Neuralgia dataneuralgia
Oats dataoats
Tuning parameter for a rho function in the (asymptotic bias-) optimal familyopt
Tuning parameter for a rho function in the (asymptotic bias-) optimal familyoptv0
Robust principal componentspcaRobS SMPCA
Robust Principal Components Cont'dprcompRob
IRWLS iterations for S- or M-estimatorsrefine.sm
Resex dataresex
Rho functionsrho
The first derivative of the rho functionrhoprime
The second derivative of the rho functionrhoprime2
M-scale estimatorscaleM
Shock datashock
Skin dataskin
SM regression estimator using Pen~a-Yohai candidatesSMPY
Stackloss datastackloss
Robust stepwise using RFPEstep.lmrobdet step.lmrobdetMM
Vehicle datavehicle
Waste datawaste
Wine datawine