Multivariate Joint Models with 'bamlss'


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Documentation for package ‘MJMbamlss’ version 0.1.0

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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