| 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 |