R: Multivariate Joint Models with 'bamlss'

# Multivariate Joint Models with 'bamlss'

## Documentation for package ‘MJMbamlss’ version 0.1.0

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

attach_wfpc | Attach Weighted Functional Principal Components to the Data
fpca | Functional principal components analysis by smoothed covariance
MFPCA_cov | Function to calculate the multivariate FPCA for a given covariance matrix and univariate basis functions
mjm_bamlss | Family for Flexible Multivariate Joint Model
MJM_predict | Prediction of MJM model
pbc_subset | PBC Subset
Predict.matrix.unc_pcre.random.effect | mgcv-style constructor for prediction of PC-basis functional random effects
preproc_MFPCA | Preprocessing step to create MFPCA object
simMultiJM | New Simulation Function For Multivariate JMs Based On FPCs
sim_bamlss_predict | Simulation Helper Function - Predict the Results for bamlss-Models
sim_jmbamlss_eval | Simulation Helper Function - Evaluate the Simulation for JMbamlss Setting
sim_jmbayes_eval | Simulation Helper Function - Evaluate the Simulation for JMbayes Setting
sim_jmb_predict | Simulation Helper Function - Predict the Results for JMbayes-Models
smooth.construct.unc_pcre.smooth.spec | mgcv-style constructor for PC-basis functional random effects (no constraint)
survint_C | Survival Integral
varbinq | Flexible Joint Models for Multivariate Longitudinal and Time-to-Event Data