model.HyndmanUllah: The Functional Demographic Model

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

Description

The Functional Demographic Model

Usage

model.HyndmanUllah(data, x, y, order = 1, transform = TRUE, ...)

Arguments

data	demogdata object. Output from read.demogdata.
x	Numerical vector indicating the ages in input data. Optional. Default: NULL.
y	Numerical vector indicating the years in input data. Optional. Default: NULL.
order	Number of basis functions to fit.
transform	If TRUE, the data are transformed with a Box-Cox transformation before the model is fitted.
...	Extra arguments passed to ftsm.

Details

\insertNoCite

hyndman2007MortalityForecast

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.HyndmanUllah

Examples

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

M <- model.HyndmanUllah(data = mx, x = x, y = y) # fit
P <- predict(M, h = 20)  # forecast
P

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