Package: MortalityLaws 3.0.0

Marius D. Pascariu

MortalityLaws: Parametric Mortality Models, Life Tables and HMD

Fit the most popular human mortality 'laws', and construct full and abridged life tables given various input indices. A mortality law is a parametric function that describes the dying-out process of individuals in a population during a significant portion of their life spans. For a comprehensive review of the most important mortality laws see Tabeau (2001) <doi:10.1007/0-306-47562-6_1>. Practical functions for downloading data from various human mortality databases are provided as well.

Authors:Marius D. Pascariu [aut, cre, cph], Vladimir Canudas-Romo [ctb]

MortalityLaws_3.0.0.tar.gz
MortalityLaws_3.0.0.zip(r-4.7-any)MortalityLaws_3.0.0.zip(r-4.6-any)MortalityLaws_3.0.0.zip(r-4.5-any)
MortalityLaws_3.0.0.tgz(r-4.6-any)MortalityLaws_3.0.0.tgz(r-4.5-any)
MortalityLaws_3.0.0.tar.gz(r-4.7-any)MortalityLaws_3.0.0.tar.gz(r-4.6-any)
MortalityLaws_3.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MortalityLaws/json (API)

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

Bug tracker:https://github.com/mpascariu/mortalitylaws/issues

Pkgdown/docs site:https://mpascariu.github.io

Datasets:
  • ahmd - MortalityLaws Test Data

On CRAN:

Conda:

actuarial-sciencedemographydownload-hmdhuman-mortality-lawslife-tablemortality

8.23 score 37 stars 2 packages 127 scripts 880 downloads 50 exports 9 dependencies

Last updated from:3cdc54db5f. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK155
source / vignettesOK180
linux-releaseOK145
macos-releaseOK130
macos-oldrelOK121
windows-develOK126
windows-releaseOK76
windows-oldrelOK92
wasm-releaseOK91

Exports:availableHMDavailableLawsavailableLFbeardbeard_makehamcarriere1carriere2convertFxdemoivredispersionggompertzgompertzgompertz_logquadgompertz0HPHP2HP3HP4invgompertzinvweibullkannistokannisto_makehamkostakiLawTableLifeTablemakehammakeham_logquadmakeham0martinelleMortalityLawneggompertzoppermanpareto_2perksquadraticReadAHMDReadCHMDReadHMDReadJMDrogersplanckscholeyscholey_shifted_powersilersteffensenstrehler_mildvanthielevandermaenvandermaen2weibullwittstein

Dependencies:askpasscurlhttrjsonlitemimeopensslpbapplyR6sys

Introduction to MortalityLaws
Welcome | Install and load | Mortality in four shapes | Getting data | Fitting a law | What comes back | Reading the figure | Fitting on a subset of ages | Age scaling | Custom laws | From fit to life table | Where to go next | sessionInfo()
Rendered fromIntro.Rmdusingknitr::rmarkdown

Last update: 2026-10-07
Started: 2018-08-16

Life tables and how MortalityLaws builds them
What a life table is | The six ways in | The count case | The rate case | Feeding columns back in | From rates to probabilities | How the columns are built | Choosing ax | The open age group | Closing and extending the table | convertFx: one indicator at a time | LawTable: a table from a law | The ex inverse: a table from life expectancies | Reading the output | Session info | References
Rendered fromLife-tables.Rmdusingknitr::rmarkdown

Last update: 2026-10-07
Started: 2026-10-05

Mortality models and estimation
What a law is | The catalogue of laws | Lifespan types | Family biographies | The Gompertz-Makeham lineage | Siler and the competing risks view | The Heligman-Pollard family | Old age: the Kannisto family | Carriere mixtures | The infant laws of Scholey | Pareto, Lomax and the power hazards | The log-quadratic family | Rogers-Planck | Heterogeneity: a note on what a fitted curve describes | Choosing among the families | Bibliographic notes | Fitting a law with MortalityLaw | The eight objectives | The optimisation procedure | Goodness of fit | How to get it wrong | Custom laws | Session info and references | References
Rendered fromMortality-models.Rmdusingknitr::rmarkdown

Last update: 2026-10-07
Started: 2026-10-05