This package is considered a duplicate. The official version of this package is found at:https://msalibian.r-universe.dev/RobStatTM

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.tar.gz(r-4.5-noble)RobStatTM_1.0.11.tar.gz(r-4.4-noble)
RobStatTM_1.0.11.tgz(r-4.4-emscripten)RobStatTM_1.0.11.tgz(r-4.3-emscripten)
RobStatTM.pdf |RobStatTM.html✨
RobStatTM/json (API)
NEWS

# 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:

alcohol - Alcohol data
algae - Algae data
biochem - Biochem data
breslow.dat - Breslow Data
bus - Bus data
flour - Flour data
glass - Glass data
hearing - Hearing data
image - Image data
leuk.dat - Leukemia Data
mineral - Mineral data
neuralgia - Neuralgia data
oats - Oats data
resex - Resex data
shock - Shock data
skin - Skin data
stackloss - Stackloss data
vehicle - Vehicle data
waste - Waste data
wine - Wine data

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

fortran openblas

5.15 score 7 packages 84 scripts 2.0k downloads 1 mentions 46 exports 7 dependencies

Last updated 2 months agofrom:1955d4c12b. Checks:OK: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Dec 17 2024
R-4.5-linux-x86_64	OK	Dec 17 2024

Exports:bisquare BYlogreg cov.dcml covClassic covRob covRobMM covRobRocke DCML fastmve huber initPP INVTR2 KurtSDNew lmrobdet.control lmrobdetDCML lmrobdetLinTest lmrobdetMM lmrobdetMM.RFPE lmrobM lmrobM.control locScaleM logregBY logregWBY logregWML MLocDis MMPY MMultiSHR mopt moptv0 Multirobu opt optv0 pcaRobS prcompRob refine.sm rho rhoprime rhoprime2 rob.linear.test RockeMulti scaleM SMPCA SMPY step.lmrobdetMM WBYlogreg WMLlogreg

Dependencies:DEoptimR lattice mvtnorm pcaPP pyinit robustbase rrcov

Optimal Bias Robust Regression Psi and Rho

Rendered fromOptimalBiasRobustRegressionPsiandRho.pdf.asisusingR.rsp::asison Dec 17 2024.

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

Polynomial Opt and mOpt Rho Functions in RobStatTM

Rendered fromPolynomialOptandmOptRhoFunctions.pdf.asisusingR.rsp::asison Dec 17 2024.

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

RobStatTM Package Vignette

Rendered fromVignetteRobStatTM.pdf.asisusingR.rsp::asison Dec 17 2024.

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

Using the fit.models Package with RobStatTM

Rendered fromfitmodelsusingRobStatTM.pdf.asisusingR.rsp::asison Dec 17 2024.

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

Help page	Topics
Alcohol data	alcohol
Algae data	algae
Biochem data	biochem
Tuning parameter the rho loss functions	bisquare
Breslow Data	breslow.dat
Bus data	bus
Approximate covariance matrix of the DCML regression estimator.	cov.dcml
Classical Covariance Estimation	covClassic
Robust multivariate location and scatter estimators	covRob Multirobu
MM robust multivariate location and scatter estimator	covRobMM MMultiSHR
Rocke's robust multivariate location and scatter estimator	covRobRocke RockeMulti
DCML regression estimator	DCML
RFPE of submodels of an 'lmrobdetMM' fit	drop1.lmrobdetMM
Minimum Volume Ellipsoid covariance estimator	fastmve
Flour data	flour
Glass data	glass
Hearing data	hearing
Tuning parameter the rho loss functions	huber
Image data	image
Robust multivariate location and scatter estimators	initPP KurtSDNew
Robust R^2 coefficient of determination	INVTR2
Leukemia Data	leuk.dat
Tuning parameters for lmrobdetMM and lmrobdetDCML	lmrobdet.control
Robust Distance Constrained Maximum Likelihood estimators for linear regression	lmrobdetDCML
Robust likelihood ratio test for linear hypotheses	lmrobdetLinTest rob.linear.test
Robust Linear Regression Estimators	lmrobdetMM
Robust Final Prediction Error	lmrobdetMM.RFPE
Robust estimators for linear regression with fixed designs	lmrobM
Tuning parameters for lmrobM	lmrobM.control
Robust univariate location and scale M-estimators	locScaleM MLocDis
Bianco and Yohai estimator for logistic regression	BYlogreg logregBY
Bianco and Yohai estimator for logistic regression	logregWBY WBYlogreg
Weighted likelihood estimator for the logistic model	logregWML WMLlogreg
Mineral data	mineral
MM regression estimator using Pen~a-Yohai candidates	MMPY
Tuning parameter for a rho function in the modified (asymptotic bias-) optimal family	mopt
Tuning parameter for a rho function in the modified (asymptotic bias-) optimal family	moptv0
Neuralgia data	neuralgia
Oats data	oats
Tuning parameter for a rho function in the (asymptotic bias-) optimal family	opt
Tuning parameter for a rho function in the (asymptotic bias-) optimal family	optv0
Robust principal components	pcaRobS SMPCA
Robust Principal Components Cont'd	prcompRob
IRWLS iterations for S- or M-estimators	refine.sm
Resex data	resex
Rho functions	rho
The first derivative of the rho function	rhoprime
The second derivative of the rho function	rhoprime2
M-scale estimator	scaleM
Shock data	shock
Skin data	skin
SM regression estimator using Pen~a-Yohai candidates	SMPY
Stackloss data	stackloss
Robust stepwise using RFPE	step.lmrobdet step.lmrobdetMM
Vehicle data	vehicle
Waste data	waste
Wine data	wine

Package: RobStatTM 1.0.11

RobStatTM: Robust Statistics: Theory and Methods

Optimal Bias Robust Regression Psi and Rho

Polynomial Opt and mOpt Rho Functions in RobStatTM

RobStatTM Package Vignette

Using the fit.models Package with RobStatTM

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)