Reference

Bayesian mortality modeling Fit and forecast mortality models
apc_stan()	Bayesian Age-Period-Cohort model with 'Stan'
cbd_stan()	Bayesian Cairns-Blake-Dowd (CBD) model with Stan
lc_stan()	Bayesian Lee-Carter with Stan
m6_stan()	Bayesian M6 model with Stan
rh_stan()	Bayesian Renshaw-Haberman model with Stan
Bayesian model averaging
mortality_weights()	Model averaging/weighting via future-out stacking or pseudo-BMA weighting
compute_weights_BMA()	Compute the model evidence/marginal likelihood via bridge sampling (or via the harmonic mean estimator if bridge sampling fails)
Functions for simulation study Useful functions to conduct simulation study
sim_death_apc()	Simulation of death counts from the Age-Period-Cohort mortality model
sim_death_cbd()	Simulation of death counts from the CBD model
sim_death_lc()	Simulation of death counts from the Lee-Carter mortality model
sim_death_m6()	Simulation of death counts from the M6 model
sim_death_mix_cbd_rh()	Simulation of death counts from a hybrid model that averages the mortality rates from the cbd and rh models
sim_death_rh()	Simulation of death counts from the Renshaw-Haberman mortality model
sim_mortality_data()	Simulation of mortality data from various models
Plotting functions
boxplot_post_dist()	Boxplot for the posterior distribution
forecasting_plot()	Fanplot for the mortality predictions
Data
FRMaleData	Deaths and Exposures Data of French Males
Functions for statistical analysis
extract_map()	Function to get the a posterior means of the parameters based on a stanfit object
fit_mo_mo()	Wrapper function to fit and forecast mortality models
Data collection
Package description
StanMoMo-package	The 'StanMoMo' package.