Package: fsdaR 0.9-0

Valentin Todorov

fsdaR: Robust Data Analysis Through Monitoring and Dynamic Visualization

Provides interface to the 'MATLAB' toolbox 'Flexible Statistical Data Analysis (FSDA)' which is comprehensive and computationally efficient software package for robust statistics in regression, multivariate and categorical data analysis. The current R version implements tools for regression: (forward search, S- and MM-estimation, least trimmed squares (LTS) and least median of squares (LMS)), for multivariate analysis (forward search, S- and MM-estimation), for cluster analysis and cluster-wise regression. The distinctive feature of our package is the possibility of monitoring the statistics of interest as a function of breakdown point, efficiency or subset size, depending on the estimator. This is accompanied by a rich set of graphical features, such as dynamic brushing, linking, particularly useful for exploratory data analysis.

Authors:Valentin Todorov [aut, cre], Emmanuele Sordini [aut], Aldo Corbellini [ctb], Francesca Torti [ctb], Marco Riani [ctb], Domenico Perrotta [ctb], Andrea Cerioli [ctb]

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fsdaR.pdf |fsdaR.html✨
fsdaR/json (API)
NEWS

# Install 'fsdaR' in R:
install.packages('fsdaR', repos = c('https://uniprjrc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/uniprjrc/fsdar/issues

Uses libs:
  • openjdk– OpenJDK Java runtime, using Hotspot JIT
Datasets:

On CRAN:

34 exports 4 stars 1.34 score 29 dependencies 93 scripts 358 downloads

Last updated 10 months agofrom:ba8394741a. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 01 2024
R-4.5-winOKSep 01 2024
R-4.5-linuxOKSep 01 2024
R-4.4-winOKSep 01 2024
R-4.4-macOKSep 01 2024
R-4.3-winOKSep 01 2024
R-4.3-macOKSep 01 2024

Exports:carbikeplotcorfwdplotcovplotfsmmmdrsfsmultFSR_controlFSReda_controlfsregfsrfanlevfwdplotLXS_controlmalfwdplotmalindexplotmdrplotmmdplotmmdrsplotmmmultMMreg_controlMMregeda_controlmyrngpsifunregspmplotresfwdplotresindexplotscoresmultspmplotSreg_controlSregeda_controltclustfsdatclustICtclustICplottclustICsoltclustreg

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrJavarlangscalestibbleutf8vctrsviridisLitewithr

Transformations in regression with fsdaR

Rendered fromfsdaR.Rnwusingutils::Sweaveon Sep 01 2024.

Last update: 2023-09-27
Started: 2022-05-11

Readme and manuals

Help Manual

Help pageTopics
Bank data (Riani et al., 2014).bank_data
Produces the carbike plot to find best relevant clustering solutions obtained by 'tclustICsol'carbikeplot
Monitoring the correlations between consecutive distances or residualscorfwdplot
Monitoring of the covariance matrixcovplot
Diabetes datadiabetes
Demographic data from the 341 miniciplaities in Emilia Romagna (an Italian region).emilia2001
Fishery data.fishery
Fleaflea
Forbes' data on air pressure in the Alps and the boiling point of water (Weisberg, 1985).forbes
Description of 'fsdalms' Objectsfsdalms.object
Description of 'fsdalts' Objectsfsdalts.object
Description of 'fsmeda.object' Objectsfsmeda.object
Performs random start monitoring of minimum Mahalanobis distancefsmmmdrs
Description of 'fsmmmdrs.object' Objectsfsmmmdrs.object
Gives an automatic outlier detection procedure in multivariate analysisfsmult
Description of 'fsmult.object' Objectsfsmult.object
Creates an 'FSR_control' objectFSR_control
Description of 'fsr' Objectsfsr.object
fsrbase: an automatic outlier detection procedure in linear regressionfsrbase fsrbase.default fsrbase.formula
Creates an 'FSReda_control' objectFSReda_control
Description of 'fsreda' Objectsfsreda.object
fsreg: an automatic outlier detection procedure in linear regressionfsreg fsreg.default fsreg.formula print.fsdalms print.fsdalts print.fsr print.fsreda print.mmreg print.mmregeda print.sreg print.sregeda
Robust transformations for regressionfsrfan fsrfan.default fsrfan.formula plot.fsrfan
Objects returned by the function 'fsrfan'fsrfan.object
Old Faithful Geyser Data.geyser2
Hawkins data.hawkins
Hospital data (Neter et al., 1996)hospital
Income1Income1
Income2Income2
Plots the trajectories of the monitored scaled (squared) residualslevfwdplot
Loyalty dataloyalty
Creates an 'LSX_control' objectLXS_control
Mixture M5 Data.M5data
Plots the trajectories of scaled Mahalanobis distances along the searchmalfwdplot
Plots the trajectory of minimum Mahalanobis distance (mmd)malindexplot
Plots the trajectory of minimum deletion residual (mdr)mdrplot
Plots the trajectory of minimum Mahalanobis distance (mmd)mmdplot
Plots the trajectories of minimum Mahalanobis distances from different starting pointsmmdrsplot
Computes MM estimators in multivariate analysis with auxiliary S-scalemmmult
Description of 'mmmult.object' Objectsmmmult.object
Description of 'mmmulteda.object' Objectsmmmulteda.object
Creates an 'MMreg_control' objectMMreg_control
Description of mmreg Objectsmmreg.object
Creates an 'MMregeda_control' objectMMregeda_control
Description of 'mmregeda' Objectsmmregeda.object
Multiple regression data showing the effect of masking (Atkinson and Riani, 2000).multiple_regression
Mussels data.mussels
Set seed for the MATLAB random number generatormyrng
Poisonpoison
Finds the tuning constant(s) associated to the supplied breakdown point or asymptotic efficiency for different psi functionspsifun
Interactive scatterplot matrix for regressionregspmplot
Plots the trajectories of the monitored scaled (squared) residualsresfwdplot
Plots the residuals from a regression analysis versus index number or any other variableresindexplot
Computes the score test for transformation in regressionscore score.default score.formula
Objects returned by the function 'score'score.object
Computes S estimators in multivariate analysissmult
Description of 'smult.object' Objectssmult.object
Description of 'smulteda.object' Objectssmulteda.object
Interactive scatterplot matrixspmplot
Creates an 'Sreg_control' objectSreg_control
Description of sreg Objectssreg.object
Creates an 'Sregeda_control' objectSregeda_control
Description of 'sregeda' Objectssregeda.object
Summary Method for 'fsdalms' objectsprint.summary.fsdalms summary.fsdalms
Summary Method for 'fsdalts' objectsprint.summary.fsdalts summary.fsdalts
Summary Method for FSR objectsprint.summary.fsr summary.fsr
Swiss banknote dataswissbanknotes
Swiss heads dataswissheads
Objects returned by the function 'tclustfsda' with the option 'monitoring=TRUE'tclusteda.object
Computes trimmed clustering with scatter restrictionstclustfsda
Objects returned by the function 'tclustfsda'tclustfsda.object
Performs cluster analysis by calling 'tclustfsda' for different number of groups 'k' and restriction factors 'c'tclustIC
Objects returned by the function 'tclustIC'tclustic.object
Plots information criterion as a function of 'c' and 'k', based on the solutions obtained by 'tclustIC'tclustICplot
Extracts a set of best relevant solutions obtained by 'tclustIC'tclustICsol
Objects returned by the function 'tclustICsol'tclusticsol.object
Computes robust linear grouping analysistclustreg
Objects returned by the function 'tclustreg'tclustreg.object
Computes 'tclustreg' for different number of groups 'k' and restriction factors 'c'.tclustregIC
Wool data.wool
Simulated data X.X
z1z1