autoSmoothAPC: Smooths demographic data using automatically estimated...

In smoothAPC: Smoothing of Two-Dimensional Demographic Data, Optionally Taking into Account Period and Cohort Effects

Description

If period and cohort effects are taken into account (effects = TRUE) the method uses all available years and diagonals for estimation of the period and cohort effects.

Usage

autoSmoothAPC(data, effects = TRUE, cornerLength = 7,
  affdDiagonals = NULL, affdYears = NULL, lower = head(c(0.01, 0.01, 0.01,
  2, 0.001, 2, 0.001), 3 + effects * 4), upper = head(c(1.2, 1.8, 1.2, 12,
  0.4, 12, 0.4), 3 + effects * 4), init = head(c(0.1, 0.1, 0.2, 4, 0.001, 4,
  0.001), 3 + effects * 4), reltol = 0.001, parameters = NULL, trace = F,
  control = list(nnzlmax = 1e+06, nsubmax = 2e+06, tmpmax = 2e+05),
  weights = NULL)

Arguments

data	Demographic data (log mortality) presented as a matrix. Row numbers represent ages and column numbers represet time.
effects	Controls if the cohort and period effects are taken into account.
cornerLength	Sets the smallest length of a diagonal to be considered for cohort effects.
affdDiagonals	Diagonals to be used for cohort effects. The first diagonal is at the bottom left corner of the data matrix (maximal age and minimal time in the data matrix).
affdYears	Years to be used for period effects.
lower	Lowest possible values for the optimization procedure.
upper	Highest possible values for the optimization procedure.
init	Initial values for the optimization procedure.
reltol	Relative tolerance parameter to be supplied to optim function.
parameters	Optional model parameters. If not provided, they are estimated.
trace	Controls if tracing is on.
control	The control data passed directly to rq.fit.sfn function.
weights	Define how much every observation effect the resulting smooth surface. The parameter must have same dimentions as data parameter. Weights can be set to reciprocal of estimated standard deviation of the data.

Value

A list of four components: smooth surface, period effects, cohort effects and parameters used for smoothing (passed as a parameter or estimated).

Author(s)

Alexander Dokumentov

References

http://robjhyndman.com/publications/mortality-smoothing/

See Also

smoothAPC and signifAutoSmoothAPC. The latter might give slightly better performance.

Examples

library(demography)
m <- log(fr.mort$rate$female[1:30, 150:160])
plot(m)
sm <- autoSmoothAPC(m)
plot(sm)
plot(sm, "period")
plot(sm, "cohort")

smoothAPC documentation built on May 2, 2019, 10:15 a.m.