Package index • vital

Create vitals

Functions for creating vital objects

vital(): Create a vital object

as_vital(): Coerce to a vital object

vital_vars(): Return vital variables

read_hmd(): Read data directly from HMD and construct a vital object for use in other functions

read_hmd_files(): Read data from files downloaded from HMD and construct a vital object for use in other functions

read_hfd(): Read data directly from HFD and construct a vital object for use in other functions

read_hfd_files(): Read data from files downloaded from HFD and construct a vital object for use in other functions

read_stmf(): Read Short-Term Mortality Fluctuations data from the Human Mortality Database

read_stmf_file(): Read STMF data from files downloaded from HMD

net_migration(): Calculate net migration from a vital object

read_ktdb(): Read old-age mortality from Kannisto-Thatcher (K-T) database and construct a vital object for use in other functions

read_ktdb_file(): #' Read old-age mortality data from files downloaded from K-T database

Data

Data sets included in the package

aus_mortality: Australian mortality data

aus_fertility: Australian fertility data

norway_births norway_fertility norway_mortality: Norwegian mortality and births data

Computing with vitals

Functions for computing on vital objects

collapse_ages(): Collapse upper ages into a single age group. Counts are summed while rates are recomputed where possible.

life_table(): Compute period life tables from age-specific mortality rates

life_expectancy(): Compute life expectancy from age-specific mortality rates

total_fertility_rate(): Compute total fertility rate from age-specific fertility rates

Smoothing

Functions for smoothing vital objects

smooth_spline() smooth_mortality() smooth_fertility() smooth_loess(): Functions to smooth demographic data

smooth_mortality_law(): Function to smooth mortality rates using MortalityLaw package

Modelling

Functions for fitting models to vitals

model(<vital>): Estimate models for vital data

GAPC() LC2() CBD() RH() APC() M7() PLAT(): Generalized APC stochastic mortality model

FDM(): Functional data model

FMEAN(): Functional mean model

FNAIVE(): Functional naive model

LC(): Lee-Carter model

Coherent models

Functions for handling coherent models

make_pr(): Do a product/ratio transformation

make_sd(): Do a sum/difference transformation

undo_pr(): Undo a product/ratio transformation

undo_sd(): Undo a mean/difference transformation

Methods for vital models

Functions that work with vital mables

forecast(<FDM>) forecast(<LC>) forecast(<GAPC>) forecast(<FMEAN>) forecast(<FNAIVE>) forecast(<mdl_vtl_df>): Produce forecasts from a vital model

generate(<mdl_vtl_df>): Generate responses from a mable

interpolate(<mdl_vtl_df>): Interpolate missing values using a vital model

age_components(): Extract age components from a model

time_components(): Extract time components from a model

cohort_components(): Extract cohort components from a model

Graphics

Plotting functions for visualizing data and models

autoplot(<mdl_vtl_df>): Plot output from a vital model

autoplot(<fbl_vtl_ts>): Plot forecasts from a vital model

autoplot(<vital>): Rainbow plot of demographic data against age

Re-exports

Exports from other packages

reexports autoplot forecast generate model report interpolate tidy augment estimate glance: Objects exported from other packages