Package: BayesMoFo 0.1.0

Jackie Siaw Tze Wong

BayesMoFo: Bayesian Mortality Forecasting

Carry out Bayesian estimation and forecasting for a variety of stochastic mortality models using vague prior distributions. Models supported include numerous well-established approaches introduced in the actuarial and demographic literature, such as the Lee-Carter (1992) <doi:10.1080/01621459.1992.10475265>, the Cairns-Blake-Dowd (2009) <doi:10.1080/10920277.2009.10597538>, the Li-Lee (2005) <doi:10.1353/dem.2005.0021>, and the Plat (2009) <doi:10.1016/j.insmatheco.2009.08.006> models. The package is designed to analyse stratified mortality data structured as a 3-dimensional array of dimensions p × A × T (strata × age × year). Stratification can represent factors such as cause of death, country, deprivation level, sex, geographic region, insurance product, marital status, socioeconomic group, or smoking behavior. While the primary focus is on analysing stratified data (p > 1), the package can also handle mortality data that are not stratified (p = 1). Model selection via the Deviance Information Criterion (DIC) is supported.

Authors:Jackie Siaw Tze Wong [aut, cre], Alex Diana [ctb], Aniketh Pittea [ctb]

BayesMoFo_0.1.0.tar.gz
BayesMoFo_0.1.0.tar.gz(r-4.7-any)BayesMoFo_0.1.0.tar.gz(r-4.6-any)
BayesMoFo_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
BayesMoFo/json (API)

# Install 'BayesMoFo' in R:

install.packages('BayesMoFo', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

jags– Just Another Gibbs Sampler for Bayesian MCMC
c++– GNU Standard C++ Library v3

Datasets:

data_summarised - Sample mortality data stratified by insurance products
dxt_array_country - Sample mortality data stratified by country
dxt_array_product - Sample mortality data stratified by insurance products
dxt_array_sex - Sample mortality data stratified by gender/sex in the UK
Ext_array_country - Sample mortality data stratified by country
Ext_array_product - Sample mortality data stratified by insurance products
Ext_array_sex - Sample mortality data stratified by gender/sex in the UK
uk_deathscausedata - Sample mortality data stratified by cause of death
uk_mortalitydata - Sample mortality data

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

jags cpp

2.70 score 574 downloads 29 exports 104 dependencies

Last updated from:571506568e. Checks:4 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	165
source / vignettes	OK	307
linux-release-x86_64	OK	162
wasm-release	OK	157

Exports:converge_diag_fn converge_diag_param_fn converge_diag_rates_fn DIC_fn fit_APCI fit_CBD_M3 fit_CBD_M5 fit_CBD_M6 fit_CBD_M7 fit_CBD_M8 fit_LC fit_M1A fit_M1M fit_M1U fit_M2A1 fit_M2A2 fit_M2Y1 fit_M2Y2 fit_MLiLee fit_PLAT fit_RH plot_deaths_fn plot_param_fn plot_rates_fn predict_deaths_fn preparedata_fn quantile_fn runBayesMoFo summary_fn

Dependencies:askpass backports base64enc bit bit64 blob broom bslib cachem callr cellranger cli clipr coda conflicted cpp11 crayon curl data.table DBI dbplyr digest dplyr dtplyr evaluate farver fastmap fontawesome forcats fs gargle generics ggplot2 glue googledrive googlesheets4 gtable haven highr hms htmltools httr ids insight isoband jquerylib jsonlite knitr labeling lattice lifecycle lubridate magrittr memoise mime modelr openssl otel pillar pkgconfig prettyunits processx progress ps purrr R6 ragg rappdirs RColorBrewer readr readxl rematch rematch2 reprex rjags rlang rmarkdown rstudioapi rvest S7 sass scales selectr stringi stringr sys systemfonts textshaping tibble tidyr tidyselect tidyverse timechange tinytex tzdb utf8 uuid vctrs viridisLite vroom withr xfun xml2 yaml

BayesMoFo-vignette

Rendered fromBayesMoFo-vignette.Rmdusingknitr::rmarkdown

Last update: 2025-07-14
Started: 2025-07-14

Help page	Topics
BayesMoFo: Bayesian Mortality Forecasting	BayesMoFo-package BayesMoFo
A function to check for overall convergence of fitted stochastic mortality models for monitoring purposes	converge_diag_fn
A function to assess convergence of the posterior sampling of fitted parameters for monitoring purposes	converge_diag_param_fn
A function to assess convergence of the posterior sampling of death rates for monitoring purposes	converge_diag_rates_fn
Sample mortality data stratified by insurance products	data_summarised
A function to calculate the DIC of stochastic mortality models using posterior samples	DIC_fn
Sample mortality data stratified by country	dxt_array_country Ext_array_country
Sample mortality data stratified by insurance products	dxt_array_product Ext_array_product
Sample mortality data stratified by gender/sex in the UK	dxt_array_sex Ext_array_sex
A function to fit the APCI stochastic mortality model.	fit_APCI
A function to fit the Age-Period-Cohort (APC) stochastic mortality model.	fit_CBD_M3
A function to fit the stochastic mortality model "M5".	fit_CBD_M5
A function to fit the stochastic mortality model "M6".	fit_CBD_M6
A function to fit the stochastic mortality model "M7".	fit_CBD_M7
A function to fit the stochastic mortality model "M8".	fit_CBD_M8
A function to fit the stochastic mortality model by Lee and Carter (1992).	fit_LC
A function to fit the stochastic mortality model M1A.	fit_M1A
A function to fit the stochastic mortality model M1M.	fit_M1M
A function to fit the stochastic mortality model M1U.	fit_M1U
A function to fit the stochastic mortality model M2A1.	fit_M2A1
A function to fit the stochastic mortality model M2A2.	fit_M2A2
A function to fit the stochastic mortality model M2Y1.	fit_M2Y1
A function to fit the stochastic mortality model M2Y2.	fit_M2Y2
A function to fit the stochastic mortality model MLiLee.	fit_MLiLee
A function to fit the stochastic mortality model "PLAT".	fit_PLAT
A function to fit the stochastic mortality model by Renshaw and Haberman (2006).	fit_RH
A function to plot the fitted and forecast number of deaths, accompanied by credible intervals, from posterior samples generated for stochastic mortality models	plot_deaths_fn
A function to plot the fitted parameters of stochastic mortality models, accompanied by credible intervals	plot_param_fn
A function to plot the fitted mortality rates, accompanied by credible intervals, from posterior samples generated for stochastic mortality models	plot_rates_fn
A function to compute the fitted and forecast number of deaths, accompanied by credible intervals, from posterior samples generated for stochastic mortality models	predict_deaths_fn
A function to prepare mortality data with stratification (e.g. by product, sex/gender, country, cause of death etc.)	preparedata_fn
A function to calculate sample quantiles	quantile_fn
A function to fit mortality models.	runBayesMoFo
A function to summarise the fitted mortality rates and parameters of stochastic mortality models	summary_fn
Sample mortality data stratified by cause of death	uk_deathscausedata
Sample mortality data	uk_mortalitydata

Package: BayesMoFo 0.1.0

BayesMoFo: Bayesian Mortality Forecasting

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)