Package: lmap 0.2.4

lmap: Logistic Mapping

Set of tools for mapping of categorical response variables based on principal component analysis (pca) and multidimensional unfolding (mdu).

Authors:Mark de Rooij [aut, cre, cph], Frank Busing [aut, cph], Juan Claramunt Gonzalez [aut]

lmap_0.2.4.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
lmap/json (API)

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

On CRAN:

Conda:

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

1.00 score 3 scripts 268 downloads 28 exports 149 dependencies

Last updated from:242be520bc. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK221
linux-devel-x86_64OK237
source / vignettesOK262
linux-release-arm64OK209
linux-release-x86_64OK226
macos-release-arm64OK188
macos-release-x86_64OK260
macos-oldrel-arm64OK180
macos-oldrel-x86_64OK352
windows-develOK161
windows-releaseOK214
windows-oldrelOK157
wasm-releaseOK150

Exports:bootstrap.clmdubootstrap.clpcabootstrap.lmdubootstrap.lpcabootstrap.mcdbootstrap.mrrrbootstrap.mruclmduclpcafastmbufastmrulmdulpcamake.df.for.varlabelsmake.dfs.for.Xmcd1mcd2mlrmrrrmruoos.comparisonprocrustes1procxread_drugdataread_isspdata_pebtheme_lmdatrioscaletwomodedistance

Dependencies:abindbackportsbase64encbitbit64bootbroombslibcachemcarcarDatacheckmateclassclicliprclustercodetoolscolorspacecorrplotcowplotcpp11crayondata.tableDerivdigestdoBydoParalleldplyre1071ellipseevaluatefarverfastmapfmdufontawesomeforcatsforeachforecastforeignFormulafracdifffsgdatagenericsggforceggplot2ggpubrggrepelggsciggsignifglmnetgluegridExtragtablegtoolshavenhighrHmischmshtmlTablehtmltoolshtmlwidgetsisobanditeratorsjomojquerylibjsonliteknitrlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmemoisemgcvmicemimeminqamitmlmodelrnlmenloptrnnetnnlsnumDerivordinalpanpbkrtestpillarpkgconfigplotrixpolyclippolynomprettyunitsprogressproxypurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRdpackreadrreformulasRfastrlangrmarkdownrpartrstatixrstudioapiS7sassscalesshapesmacofSparseMstringistringrsurvivalsystemfontstibbletidyrtidyselecttimeDatetinytextweenrtzdbucminfurcautf8vctrsviridisLitevroomweightswithrwordcloudxfunyamlziggzoo

Readme and manuals

Help Manual

Help pageTopics
Bootstrap procedure for Cumulative Logistic (Restricted) MDUbootstrap.clmdu
Bootstrap procedure for Cumulative Logistic (Restricted) PCAbootstrap.clpca
Bootstrap procedure for Logistic (Restricted) MDUbootstrap.lmdu
Bootstrap procedure for Logistic (Restricted) PCAbootstrap.lpca
Bootstrap procedure for Multonimal Canonical Decomposition Modelbootstrap.mcd
Bootstrap procedure for Multinomial Reduced Rank Modelbootstrap.mrrr
Bootstrap procedure for Multinomial Restricted Unfoldingbootstrap.mru
Cumulative Logistic (Restricted) MDUclmdu
Cumulative Logistic (Restricted) PCAclpca
Dummy data for clmdu exampledataExample_clmdu
Dummy data for clpca exampledataExample_clpca
Dummy data for lmdu exampledataExample_lmdu
Dummy data for lpca exampledataExample_lpca
Dummy data for mru exampledataExample_mru
Diabetes datadiabetes
Dutch Parliamentary Election Studydpes
Fast version of mbu. It runs mbu without input checks.fastmbu
Fast version of mru. It runs mru without input checks.fastmru
Kieskompas datakieskompas
Liverliver
Logistic (Restricted) MDUlmdu
Logistic (Restricted) PCAlpca
Helper function for the plot functionsmake.df.for.varlabels
Helper function for the plot functionsmake.dfs.for.X
Multinomial Canonical Decomposition Model for Multivariate Binary Datamcd1
Multinomial Canonical Decomposition Model for a multinomial outcomemcd2
Multinomial Logistic Regressionmlr
Multinomial Reduced Rank Regressionmrrr
Multinomial Restricted MDUmru
Netherlands Study for Depression and Anxietynesda
This function compares the predictive performance of several models fitted on the same dataoos.comparison
Plot an object obtained using one of the bootstrap functionsplot.bootstrap
Plots a Cumulative Logistic MDU modelplot.clmdu
Plots a Cumulative Logistic PCA modelplot.clpca
Plots a Logistic MDU modelplot.lmdu
Plots a Logistic PCA Modelplot.lpca
Plots a Multinomial Reduced Rank Modelplot.mrrr
Plots a Multinomial Restricted MDU modelplot.mru
Plotting function for object of class trioscaleplot.trioscale
The function predict.clmdu makes predictions for a test/validation set based on a fitted cl restricted multidimensional unfolding model (clmdu with X)predict.clmdu
The function predict.clpca makes predictions for a test/validation set based on a fitted clrrr model (clpca with X)predict.clpca
The function predict.lmdu makes predictions for a test/validation set based on a fitted lrmdu model (lmdu with X)predict.lmdu
The function predict.lpca makes predictions for a test/validation set based on a fitted lrrr model (lpca with X)predict.lpca
The function predict.mlr makes predictions for a test/validation set based on a fitted mlr modelpredict.mlr
The function predict.mrrr makes predictions for a test/validation set based on a fitted mrrr modelpredict.mrrr
The function predict.mru makes predictions for a test/validation set based on a fitted mru modelpredict.mru
Two procedures for procrustes analysisprocrustes1
Helper function for pre-processing the predictorsprocx
Function for reading the drug consumption data from the UCI repositoryread_drugdata
Function to read in the ISSP data It requires the file ZA7650_v1-0-0.sav to be on your computer this file can be obtained from /www.gesis.org/en/issp/modules/issp-modules-by-topic/environment/2020 ZA7650 Data file Version 1.0.0, https://doi.org/10.4232/1.13921.read_isspdata_peb
Summarizing Cumulative Logistic MDU models The function summary.lmdu gives a summary from an object from clmdu()summary.clmdu
Summarizing Cumulative Logistic PCA modelssummary.clpca
Summarizing Logistic MDU modelssummary.lmdu
Summarizing Logistic PCA modelssummary.lpca
Summarizing an Multinomial Canonical Decomposition Modelsummary.mcd
Summarizing Multinomial Logistic Regression Modelsummary.mlr
Summarizing Multinomial Reduced Rank Modelsummary.mrrr
Summarizing Multinomial Restricted Unfolding Model The function summary.mru gives a summary from an object from mru()summary.mru
Summarizing TrioScalesummary.trioscale
Theme_lmdatheme_lmda
Function for TRIOSCALEtrioscale
The function twomodedistance computes the two mode (unfolding) distancetwomodedistance