Description Usage Arguments Value Author(s) References See Also Examples
View source: R/auto.l1tp.smooth.R
It is a heuristic procedure which tries to figure out positions of
period and cohort effects in the data. It also uses a few steps to estimate
model's parameters. The procedure is supposed to outperform autoSmoothAPC
slightly.
1 2 3 4 5 | signifAutoSmoothAPC(data, p.value = 0.05, cornerLength = 7,
lower = c(0.01, 0.01, 0.01, 1, 0.001, 1, 0.001), upper = c(1.2, 1.8, 1.2,
12, 0.4, 12, 0.4), init = c(0.1, 0.1, 0.2, 4, 0.001, 4, 0.001),
reltol = 0.001, trace = F, control = list(nnzlmax = 1e+06, nsubmax =
2e+06, tmpmax = 2e+05), weights = NULL)
|
data |
Demographic data (log mortality) presented as a matrix. Row numbers represent ages and column numbers represet time. |
p.value |
P-value used to test the period and the cohort effects for significance. The lower the value the fewer diagonals and years will be used to find cohort and period effects. |
cornerLength |
Minimal length of a diagonal to be considered for cohort 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 |
trace |
Controls if tracing is on. |
control |
The control data passed directly to |
weights |
Define how much every observation effect the resulting smooth surface.
The parameter must have same dimentions as |
A list of six components: smooth surface, period effects, cohort effects, parameters used for smoothing, diagonals used for cohort effects and years used for period effects.
Alexander Dokumentov
http://robjhyndman.com/publications/mortality-smoothing/
1 2 3 4 5 6 7 8 |
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