Fit PAR model using sample autocorrelations
num2pcpar.Rd
Fit PAR model using sample autocorrelations.
Arguments
- x
time series, a numeric vector.
- order
PAR order, a single number or a vector with one entry for each season.
- result
what to return, the default is to return the full model, see Details.
- ...
passed on to
calc_peracf
.
Details
Computes the periodic autocorrelations and fits a PAR model using the Periodic Levinson-Durbin algorithm.
The order is a vector of non-negative integers, specifying the
autoregressive orders for each season. If order
is a single
number, then all seasons have that order.
mean
controls centering in the computation of the
autocorrelations. If mean
is numeric, then subtract the
supplied mean before computing the autocovariances. If mean
is
TRUE, the default, compute and subtract the sample periodic mean
before computing the autocovariances. If mean
is FALSE, do not
centre the series, i.e. assume that the mean is zero.
If result
is NULL, the default, returns the full model. If
result = "coef"
, returns the PAR coefficients only (currently
any value of result
other than NULL has this effect).
Value
The coefficients of the fitted model or a list with components:
- mean
the mean, set as described in Details.
- coef
forward prediction coefficients.
- scale
standard deviations of the innovations.
See also
fitPM
which uses num2pcpar
for calculations
Examples
if (FALSE) {
simts1 <- matrix(rnorm(100), nrow = 4)
num2pcpar(simts1, order = c(3,2,2,2), period = 4 )
num2pcpar(simts1, order = c(3,2,1,2), period = 4 )
pdSafeParOrder(c(3,2,1,2))
pdSafeParOrder(c(3,2,2,1))
num2pcpar(simts1, order = c(3,2,2,1), period = 4 )
num2pcpar(simts1, order = pdSafeParOrder(c(3,2,2,1)), period = 4 )
num2pcpar(simts1, order = c(3,2,1,2), period = 4 )
num2pcpar(simts1, order = c(3,2,1,2), period = 4, mean = rep(0,4) )
num2pcpar(simts1, order = c(3,2,1,2), period = 4, mean = FALSE )
num2pcpar(simts1, order = c(3,2,1,2), period = 4, mean = FALSE )$coef@m -
num2pcpar(simts1, order = c(3,2,1,2), period = 4 )$coef@m
}