c(
person("Marius D.", "Pascariu", role = c("aut", "cre", "cph"), email = "mpascariu@outlook.com", comment = c(ORCID = "0000-0002-2568-6489")),
person("Vladimir", "Canudas-Romo", role = "ctb"))
Marius D. Pascariu [aut, cre, cph]
(<https://orcid.org/0000-0002-2568-6489>),
Vladimir Canudas-Romo [ctb]

Fit the most popular human mortality 'laws', and construct
full and abridge 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.

Smoothing one- and two-dimensional Poisson counts with
P-splines specifically tailored to mortality data.
Extra-Poisson variation can be accounted. Collection of
mortality data and a specific function for selecting those data
by country, sex, age and years.

Smoothing and forecasting Poisson counts with P-splines
Smoothing one- and two-dimensional Poisson counts with
P-splines specifically tailored to mortality data.
Extra-Poisson variation can be accounted as well as
forecasting. Collection of mortality data and a specific
function for selecting those data by country, sex, age and
years.

Smoothing one- and two-dimensional Poisson counts with
P-splines specifically tailored to mortality data.
Extra-Poisson variation can be accounted as well as
forecasting.  Collection of mortality data and a specific
function for selecting those data by country, sex, age and
years.

Smoothing one- and two-dimensional Poisson counts with
P-splines specifically tailored to mortality data.
Extra-Poisson variation can be accounted as well as forecasting.
Collection of mortality data and a specific function for
selecting those data by country, sex, age and years.

Smoothing and Forecasting Poisson Counts with P-Splines

A Framework for Various Types of Mortality / Life Tables
Classes to implement and plot cohort life tables
for actuarial calculations. In particular, birth-year dependent mortality
tables using a yearly trend to extrapolate from a base year are implemented,
as well as period life table, cohort life tables using an age shift, and
merged life tables.
'mortalityTable.R' 'mortalityTable.period.R'
'mortalityTable.ageShift.R' 'ageShift.R'
'mortalityTable.observed.R' 'mortalityTable.joined.R'
'mortalityTable.mixed.R' 'ages.R' 'baseTable.R' 'baseYear.R'
'fillAges.R' 'pensionTable.R' 'commutationNumbers.R'
'mortalityTable.improvementFactors.R'
'mortalityTable.trendProjection.R' 'deathProbabilities.R'
'getCohortTable.R' 'getOmega.R' 'getPeriodTable.R'
'lifeTable.R' 'makeQxDataFrame.R' 'mortalityComparisonTable.R'
'mortalityImprovement.R' 'mortalityTable.MakehamGompertz.R'
'mortalityTable.Weibull.R' 'mortalityTable.deMoivre.R'
'periodDeathProbabilities.R' 'mortalityTable.jointLives.R'
'mortalityTables.list.R' 'mortalityTables.load.R'
'plot.mortalityTable.R' 'plotMortalityTableComparisons.R'
'plotMortalityTables.R' 'plotMortalityTrend.R' 'setLoading.R'
'setModification.R' 'undampenTrend.R'
'whittaker.mortalityTable.R'