# Logistic Mapping

## Documentation for package ‘lmap’ version 0.2.4

- DESCRIPTION file.

## Help Pages

bootstrap.clmdu | Bootstrap procedure for Cumulative Logistic (Restricted) MDU
bootstrap.clpca | Bootstrap procedure for Cumulative Logistic (Restricted) PCA
bootstrap.lmdu | Bootstrap procedure for Logistic (Restricted) MDU
bootstrap.lpca | Bootstrap procedure for Logistic (Restricted) PCA
bootstrap.mcd | Bootstrap procedure for Multonimal Canonical Decomposition Model
bootstrap.mrrr | Bootstrap procedure for Multinomial Reduced Rank Model
bootstrap.mru | Bootstrap procedure for Multinomial Restricted Unfolding
clmdu | Cumulative Logistic (Restricted) MDU
clpca | Cumulative Logistic (Restricted) PCA
dataExample_clmdu | Dummy data for clmdu example
dataExample_clpca | Dummy data for clpca example
dataExample_lmdu | Dummy data for lmdu example
dataExample_lpca | Dummy data for lpca example
dataExample_mru | Dummy data for mru example
diabetes | Diabetes data
dpes | Dutch Parliamentary Election Study
fastmbu | Fast version of mbu. It runs mbu without input checks.
fastmru | Fast version of mru. It runs mru without input checks.
kieskompas | Kieskompas data
liver | Liver
lmdu | Logistic (Restricted) MDU
lpca | Logistic (Restricted) PCA
make.df.for.varlabels | Helper function for the plot functions
make.dfs.for.X | Helper function for the plot functions
mcd1 | Multinomial Canonical Decomposition Model for Multivariate Binary Data
mcd2 | Multinomial Canonical Decomposition Model for a multinomial outcome
mlr | Multinomial Logistic Regression
mrrr | Multinomial Reduced Rank Regression
mru | Multinomial Restricted MDU
nesda | Netherlands Study for Depression and Anxiety
oos.comparison | This function compares the predictive performance of several models fitted on the same data
plot.bootstrap | Plot an object obtained using one of the bootstrap functions
plot.clmdu | Plots a Cumulative Logistic MDU model
plot.clpca | Plots a Cumulative Logistic PCA model
plot.lmdu | Plots a Logistic MDU model
plot.lpca | Plots a Logistic PCA Model
plot.mrrr | Plots a Multinomial Reduced Rank Model
plot.mru | Plots a Multinomial Restricted MDU model
plot.trioscale | Plotting function for object of class trioscale
predict.clmdu | The function predict.clmdu makes predictions for a test/validation set based on a fitted cl restricted multidimensional unfolding model (clmdu with X)
predict.clpca | The function predict.clpca makes predictions for a test/validation set based on a fitted clrrr model (clpca with X)
predict.lmdu | The function predict.lmdu makes predictions for a test/validation set based on a fitted lrmdu model (lmdu with X)
predict.lpca | The function predict.lpca makes predictions for a test/validation set based on a fitted lrrr model (lpca with X)
predict.mlr | The function predict.mlr makes predictions for a test/validation set based on a fitted mlr model
predict.mrrr | The function predict.mrrr makes predictions for a test/validation set based on a fitted mrrr model
predict.mru | The function predict.mru makes predictions for a test/validation set based on a fitted mru model
procrustes1 | Two procedures for procrustes analysis
procx | Helper function for pre-processing the predictors
read_drugdata | Function for reading the drug consumption data from the UCI repository
read_isspdata_peb | 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.
summary.clmdu | Summarizing Cumulative Logistic MDU models The function summary.lmdu gives a summary from an object from clmdu()
summary.clpca | Summarizing Cumulative Logistic PCA models
summary.lmdu | Summarizing Logistic MDU models
summary.lpca | Summarizing Logistic PCA models
summary.mcd | Summarizing an Multinomial Canonical Decomposition Model
summary.mlr | Summarizing Multinomial Logistic Regression Model
summary.mrrr | Summarizing Multinomial Reduced Rank Model
summary.mru | Summarizing Multinomial Restricted Unfolding Model The function summary.mru gives a summary from an object from mru()
summary.trioscale | Summarizing TrioScale
theme_lmda | Theme_lmda
trioscale | Function for TRIOSCALE
twomodedistance | The function twomodedistance computes the two mode (unfolding) distance