Package: BayesMortalityPlus 0.2.4

Luiz Fernando Figueiredo

BayesMortalityPlus: Bayesian Mortality Modelling

Fit Bayesian graduation mortality using the Heligman-Pollard model, as seen in Heligman, L., & Pollard, J. H. (1980) <doi:10.1017/S0020268100040257> and Dellaportas, Petros, et al. (2001) <doi:10.1111/1467-985X.00202>, and dynamic linear model (Campagnoli, P., Petris, G., and Petrone, S. (2009) <doi:10.1007/b135794_2>). 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) <https://www.jstor.org/stable/48547511>. 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) <doi:10.1080/01621459.1992.10475265> and Pedroza, C. (2006) <doi:10.1093/biostatistics/kxj024>.

Authors:Laboratorio de Matematica Aplicada

BayesMortalityPlus_0.2.4.tar.gz
BayesMortalityPlus_0.2.4.tar.gz(r-4.5-noble)BayesMortalityPlus_0.2.4.tar.gz(r-4.4-noble)
BayesMortalityPlus_0.2.4.tgz(r-4.4-emscripten)BayesMortalityPlus_0.2.4.tgz(r-4.3-emscripten)
BayesMortalityPlus.pdf |BayesMortalityPlus.html
BayesMortalityPlus/json (API)

# Install 'BayesMortalityPlus' in R:
install.packages('BayesMortalityPlus', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • PT - Mortality Data from Portugal to be used as example
  • USA - Mortality Database from United States to be used as example

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

1.48 score 1 scripts 647 downloads 10 exports 41 dependencies

Last updated 7 months agofrom:148b1c74e3. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 02 2024
R-4.5-linuxOKDec 02 2024

Exports:blcdlmdlm_closeexpectancyHeatmaphphp_closehp_miximprovementplot_chain

Dependencies:clicolorspacecpp11crayondplyrfansifarvergenericsggplot2gluegtablehmsisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellmvtnormnlmepillarpkgconfigprettyunitsprogresspurrrR6RColorBrewerrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Lee-Carter Bayesian Estimation for mortality datablc
Dynamic Linear Model for mortality table graduationdlm
DLM: Fitting the advanced ages of the life tablesdlm_close
Generic expectancy functionexpectancy
BLC: Life expectancyexpectancy.BLC
DLM: Life expectancyexpectancy.DLM
HP: Life expectancyexpectancy.HP
BLC: Fitted death probabilities (qx)fitted.BLC
DLM: Fitted death probabilities (qx)fitted.DLM
HP: Fitted death probabilities (qx)fitted.HP
Generic Heatmap functionHeatmap
BLC: Heatmap for the life expectancyHeatmap.BLC
DLM: Heatmap for the life expectancyHeatmap.DLM
HP: Heatmap for the life expectancyHeatmap.HP
Heatmap for a set of life tablesHeatmap.list
Bayesian Heligman-Pollard curve for mortality table graduationhp
HP: Fitting the advanced ages of the life tableshp_close
HP: Model mixturehp_mix
BLC: Improvementimprovement
BLC: Arithmetic meanmean.BLC
BLC: Arithmetic mean for predictionsmean.PredBLC
Chain's plotplot_chain
BLC: Plot the fitted valuesplot.BLC
DLM: Plot the life tableplot.DLM
HP: Plot the life tableplot.HP
Plot a set of life tablesplot.list
BLC: Plot the log-mortality of a predictionplot.PredBLC
BLC: Forecastingpredict.BLC
DLM: Prediction of death probabilitypredict.DLM
BLC: Printprint.BLC
DLM: Printprint.DLM
HP: Printprint.HP
Mortality Data from Portugal to be used as examplePT
BLC: Sample quantilesquantile.BLC
BLC: Sample quantiles for predictionsquantile.PredBLC
DLM: Summarysummary.DLM
HP: Summarysummary.HP
Mortality Database from United States to be used as exampleUSA