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BayesMortalityPlus  

Bayesian Mortality Modelling
View on CRAN: Click here


Download and install BayesMortalityPlus package within the R console
Install from CRAN:
install.packages("BayesMortalityPlus")

Install from Github:
library("remotes")
install_github("cran/BayesMortalityPlus")

Install by package version:
library("remotes")
install_version("BayesMortalityPlus", "0.2.4")



Attach the package and use:
library("BayesMortalityPlus")
Maintained by
Luiz Fernando Figueiredo
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-05-09
Latest Update: 2024-02-02
Description:
Fit Bayesian graduation mortality using the Heligman-Pollard model, as seen in Heligman, L., & Pollard, J. H. (1980) and Dellaportas, Petros, et al. (2001) , and dynamic linear model (Campagnoli, P., Petris, G., and Petrone, S. (2009) ). While Heligman-Pollard has parameters with a straightforward interpretation yielding some rich analysis, the dynamic linear model provides a very flexible adjustment of the mortality curves by controlling the discount factor value. Closing methods for both Heligman-Pollard and dynamic linear model were also implemented according to Dodd, Erengul, et al. (2018) . The Bayesian Lee-Carter model is also implemented to fit historical mortality tables time series to predict the mortality in the following years and to do improvement analysis, as seen in Lee, R. D., & Carter, L. R. (1992) and Pedroza, C. (2006) .
How to cite:
Luiz Fernando Figueiredo (2023). BayesMortalityPlus: Bayesian Mortality Modelling. R package version 0.2.4, https://cran.r-project.org/web/packages/BayesMortalityPlus. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.1.0 (2023-05-09 11:30), 0.1.1 (2023-09-06 15:10), 0.2.2 (2024-02-02 18:20), 0.2.3 (2024-03-04 17:50)
Other packages that cited BayesMortalityPlus R package
View BayesMortalityPlus citation profile
Other R packages that BayesMortalityPlus depends, imports, suggests or enhances
Complete documentation for BayesMortalityPlus
Functions, R codes and Examples using the BayesMortalityPlus R package
Some associated functions: Heatmap.BLC . Heatmap.DLM . Heatmap.HP . Heatmap.list . Heatmap . PT . USA . blc . dlm . dlm_close . expectancy.BLC . expectancy.DLM . expectancy.HP . expectancy . fitted.BLC . fitted.DLM . fitted.HP . hp . hp_close . hp_mix . improvement . mean.BLC . mean.PredBLC . plot.BLC . plot.DLM . plot.HP . plot.PredBLC . plot.list . plot_chain . predict.BLC . predict.DLM . print.BLC . print.DLM . print.HP . quantile.BLC . quantile.PredBLC . summary.DLM . summary.HP . 
Some associated R codes: Heatmap_default.R . PT.R . USA.R . blc.R . dlm.R . dlm_close.R . expectancy_blc.R . expectancy_default.R . expectancy_dlm.R . expectancy_hp.R . ffbs.R . fitted_blc.R . fitted_dlm.R . fitted_hp.R . fun_aux.R . globals.R . gompertz_dlm.R . heatmap_blc.R . heatmap_dlm.R . heatmap_hp.R . heatmap_list.R . hp.R . hp_binomial.R . hp_binomial_reduced.R . hp_close.R . hp_lognormal.R . hp_lognormal_reduced.R . hp_mix.R . hp_poisson.R . hp_poisson_reduced.R . improvement.R . kd_filter.R . kd_smoother.R . mean_blc.R . mean_blc_pred.R . plot_blc.R . plot_blc_pred.R . plot_chain.R . plot_dlm.R . plot_hp.R . plot_list.R . predict_blc.R . predict_dlm.R . print_blc.R . print_blc_pred.R . print_dlm.R . print_hp.R . quantile_blc.R . quantile_blc_pred.R . sir_gompertz.R . summary_dlm.R . summary_hp.R .  Full BayesMortalityPlus package functions and examples
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