model.LeeCarter: The Lee-Carter Mortality Model

In mpascariu/MortalityForecast: Standard Tools to Compare and Evaluate Various Mortality Forecasting Methods

Description

Fit the Lee-Carter mortality model

Usage

model.LeeCarter(data, x = NULL, y = NULL, verbose = TRUE, ...)

Arguments

data	A data.frame or a matrix containing mortality data with ages x as row and time y as column.
x	Numerical vector indicating the ages in input data. Optional. Default: NULL.
y	Numerical vector indicating the years in input data. Optional. Default: NULL.
verbose	A logical value. Set verbose = FALSE to silent the process that take place inside the function and avoid progress messages.
...	Arguments to be passed to or from other methods.

Details

\insertNoCite

lee1992MortalityForecast

Value

The output is a list with the components:

input	List with arguments provided in input. Saved for convenience;
info	Short details about the model;
call	An unevaluated function call, that is, an unevaluated expression which consists of the named function applied to the given arguments;
coefficients	Estimated coefficients;
fitted.values	Fitted values of the estimated model;
observed.values	The observed values used in fitting arranged in the same format as the fitted.values;
residuals	Deviance residuals;
x	Vector of ages used in the fitting;
y	Vector of years used in the fitting.

References

\insertAllCited

See Also

predict.LeeCarter

Examples

# Data
x  <- 0:89
y  <- 1985:2014
mx <- HMD_male$mx$GBRTENW[paste(x), paste(y)]

# Fit the model
M <- model.LeeCarter(data = mx, x = x, y = y)
M
summary(M)

# Check residuals
R <- residuals(M)

plot(R, plotType = "scatter")
plot(R, plotType = "colourmap")
plot(R, plotType = "signplot")

# Forecast 
P <- predict(M, h = 20)
P

mpascariu/MortalityForecast documentation built on Sept. 28, 2020, 2:40 p.m.