Package: BayesMoFo
Title: Bayesian Mortality Forecasting
Version: 0.1.0
Authors@R: 
  c(person(given = c("Jackie", "Siaw", "Tze"), 
 	   family = "Wong", 
	   role = c("aut", "cre"), 
	   email = "jw19203@essex.ac.uk", 
	   comment = c(ORCID = "0000-0002-0314-6684")),
    person(given = "Alex", 
	   family = "Diana", 
	   role = "ctb", 
	   email = "ad23269@essex.ac.uk"),
    person(given = "Aniketh", 
	   family = "Pittea", 
	   role = "ctb", 
	   email = "aniketh.pittea@uk.gt.com"))
Description: 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.
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 7.3.2
Imports: rjags, insight, coda, tidyverse, dplyr, magrittr, rlang
Depends: R (>= 4.0.0)
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-07-10 00:19:50 UTC; Jackie
Author: Jackie Siaw Tze Wong [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-0314-6684>),
  Alex Diana [ctb],
  Aniketh Pittea [ctb]
Maintainer: Jackie Siaw Tze Wong <jw19203@essex.ac.uk>
Repository: CRAN
Date/Publication: 2025-07-14 17:30:06 UTC
Built: R 4.4.3; ; 2026-03-27 22:37:30 UTC; windows
