# season

##### Seasonal Adjustment

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.

- trade
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:

variance of the system noise.

variance of the observational noise.

log-likelihood of the model.

AIC of the model.

trend component (for `trend.order`

> 0).

seasonal component (for `seasonal.order`

> 0).

AR coefficients (for `ar.order`

> 0).

AR component (for `ar.order`

> 0).

trading day effect (for `trade`

= 6).

noise component.

covariance matrix of smoother.

##### References

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

##### 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)*