wilmoth: Fit the Log-Quadratic Model

In mpascariu/MortalityEstimate: Indirect Estimation Methods for Measurement of Demographic Indicators

Description

Estimate the Log-Quadratic model. The implemented estimation using the bi-weight procedure is described in the Appendix of \insertCitewilmoth2012;textualMortalityEstimate

Usage

wilmoth(x, mx = NULL, LT = NULL, verbose = TRUE, control = list())

Arguments

x	Numerical vector containing ages corresponding to the input data (in 'mx' or 'LT').
mx	Input data. A data.frame / matrix with death rates.
LT	Input data. A collection of life tables. If mx is provided LT is not necessary and vice versa.
verbose	Logical. Choose whether to display a progress bar during the fitting process. Default: TRUE.
control	List with additional parameters. See wilmoth_control.

Value

The output is of class wilmoth with the components:

input	A list with input objects provided in the function;
call	An unevaluated function call, that is, an unevaluated expression which consists of the named function applied to the given arguments;
coefficients	Estimated coefficients;
k	The estimated k parameter;
fitted.values	Fitted values of the estimated model;
residuals	Deviance residuals;
model.info	Model details (equation). The relationship between the death rate at age x, and the probability of dying between birth and age 5.

References

\insertAllCited

See Also

wilmothLT

Examples

## Not run: 
# DATA
HMD719f <- HMD719[HMD719$sex == "female", ]

# Fit model
x <- c(0,1, seq(5, 110, by = 5))
W <- wilmoth(x, LT = HMD719f)

## End(Not run)

mpascariu/MortalityEstimate documentation built on May 11, 2021, 6:33 p.m.