pclsdf | R Documentation |
Fit PAR models using least squares. The model may contain intercepts and linear trends, seasonal or non-seasonal.
pclsdf(x, d, lags = integer(0), sintercept = TRUE, sslope = FALSE,
intercept = FALSE, slope = FALSE, xreg, contrasts = NULL,
seasonof1st = NULL, coefonly = FALSE)
x |
time series, a numeric vector. |
d |
period, an integer. |
lags |
an integer vector, typically |
sintercept |
if TRUE include seasonal intercepts. |
sslope |
if TRUE include seasonal linear trend. |
intercept |
if TRUE include non-seasonal intercept. |
slope |
if TRUE include non-seasonal linear trend. |
xreg |
additional regressors, not used currently. |
contrasts |
contrasts to use for the seasons factor variable. |
seasonof1st |
season of the first observation in the time series, see Details. |
coefonly |
if TRUE, return only the parameters of the fitted
model, otherwise include also the object returned by |
This function fits PAR models by the method of least squares. Seasonal intercepts are included by default. Non-seasonal intercepts are available, as well as seasonal and non-seasonal linear trend. Separate arguments are provided, so that any combination of seasonal and non-seasonal intercepts and slopes can be specified.
If coefonly
is TRUE, pclsdf
returns only the estimated
parameters, otherwise it includes additional statistical information,
see section Note for the current details.
A list with the components listed below. Some components are present only if included in the model specification.
par |
the PAR coefficients, a matrix with a row for each season. |
sintercept |
(if specified) seasonal intercepts, a numeric vector. |
sigma2hat |
innovation variances. |
formula.char |
the formula used in the call of |
fit |
(if |
Currently, pclsdf
prepares a model formula according to the
specification and calls lm
to do the fitting. Component "fit"
in the result (available when coefonly = FALSE
) contains the
raw fitted object returned by lm
. Statistical inference based
on this object would, in general, not be justified for correlated
data.
todo: currently some of the parameters are returned only via the
fitted object from lm
.
Georgi N. Boshnakov
pclspiar
,
## data(dataFranses1996)
cu <- pcts(dataFranses1996[ , "CanadaUnemployment"])
cu <- window(cu, start = availStart(cu), end = availEnd(cu))
pclsdf(cu, 4, 1:2, sintercept = TRUE)
pclsdf(austres, 4, lags = 1:3)
pclsdf(austres, 4, lags = 1:3, sintercept = TRUE)
pclsdf(austres, 4, lags = 1:3, sintercept = TRUE, sslope = TRUE)
x <- rep(1:4,10)
pclsdf(x, 4, lags = 1:3, sintercept = TRUE, sslope = TRUE)
## this is for the version when contrasts arg. was passed on directly to lm.
## tmp1 <- pclsdf(austres, 4, lags = 1, sintercept = FALSE, sslope = TRUE,
## contrasts = list(Season = "contr.sum" ))
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