season

0th

Percentile

Seasonal adjustment by state space modeling.

Keywords
ts
Usage
season(y, trend.order = 1, seasonal.order = 1, ar.order = 0, trade = FALSE,
period = 12, tau2.ini = NULL, filter = c(1, length(y)),
predict = length(y), arcoef.ini = NULL, log = FALSE,
minmax = c(-1.0e+30, 1.0e+30), plot = TRUE, ...)
Arguments
y

a univariate time series.

trend.order

trend order.

seasonal.order

seasonal order.

ar.order

AR order.

logical; if TRUE, the model including trading day effect component is considered, where tsp(y) is not NULL and frequency(y) is 4 or 12.

period

number of seasons in one period. If the tsp attribute of y is not NULL, frequency(y).

 = 12 : for monthly data = 12 : for monthly data
tau2.ini

initial estimate of variance of the system noise $\tau^2$, not equal to 1.

filter

a numerical vector of the form c(x1,x2) which gives start and end position of filtering.

predict

the end position of prediction ($\geq$ x2).

arcoef.ini

initial estimate of AR coefficients (for ar.order > 0).

log

logical. If TRUE, the data y is log-transformed.

minmax

lower and upper limits of observations.

plot

logical. If TRUE (default), 'trend', 'seasonal' and 'ar' are plotted.

further arguments to be passed to plot.season.

Value

An object of class "season", which is a list with the following elements:

tau2

variance of the system noise.

sigma2

variance of the observational noise.

llkhood

log-likelihood of the model.

aic

AIC of the model.

trend

trend component (for trend.order > 0).

seasonal

seasonal component (for seasonal.order > 0).

arcoef

AR coefficients (for ar.order > 0).

ar

AR component (for ar.order > 0).

day.effect

trading day effect (for trade = 6).

noise

noise component.

cov

covariance matrix of smoother.

References

Kitagawa, G. (2010) Introduction to Time Series Modeling. Chapman & Hall/CRC.

• season
Examples
# NOT RUN {
# BLSALLFOOD data
data(BLSALLFOOD)
season(BLSALLFOOD, trend.order = 2, seasonal.order = 1, ar.order = 2)

season(BLSALLFOOD, trend.order = 2, seasonal.order = 1, ar.order = 2,
filter = c(1, 132))

# Wholesale hardware data
data(WHARD)
season(WHARD, trend.order = 2, seasonal.order = 1, ar.order = 0, trade = TRUE,
log = TRUE)

season(WHARD, trend.order = 2, seasonal.order = 1, ar.order = 0, trade = TRUE,
filter = c(1, 132), log = TRUE)
# }

Documentation reproduced from package TSSS, version 1.2.3, License: GPL (>= 2)

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