Decomposes a time series represented by an `inz_ts`

object into its
seasonal, trend, and remainder components using the specified smoothing
method.

```
decomp(
x,
var = NULL,
sm_model = c("stl"),
mult_fit = FALSE,
model_range = NULL,
...
)
# S3 method for inz_dcmp
plot(
x,
recompose.progress = c(0, 0),
recompose = any(recompose.progress > 0),
ylab = NULL,
title = NULL,
colour = c("#1B9E46", "#45a8ff", "orangered"),
...
)
```

## Arguments

- x
An `inz_dcmp` object representing the decomposed time series.

- var
A character vector of length one, or `NULL`

.

- sm_model
The smoothing method to be used.
Currently on "stl" is available.

- mult_fit
If `TRUE`

, a multiplicative model is used; otherwise,
an additive model is used by default.

- model_range
The range of data to be decomposed by the model. It can be
specified as dates or years. If part of `model_range`

lies
outside the range of the data, the exceeding proportion is ignored.

- ...
Additional arguments (ignored).

- recompose.progress
A numeric vector of length 2, controlling the
display of recomposition progress when `recompose` is `TRUE`.
The first component shows the progress for the seasonal component
(0 to 1), and the second component tracks the number of observations
recomposed so far.

- recompose
Logical indicating whether the recomposition should be
displayed or not.

- ylab
The label for the y-axis of the plot.

- title
The title for the plot.

- colour
A vector of three colors specifying the colors for the trend,
seasonal, and residuals components, respectively.

## Value

An `inz_dcmp`

object, which is a sub-class of `dable`

,
representing the decomposed components of the time series.

## References

R. B. Cleveland, W. S. Cleveland, J.E. McRae, and I. Terpenning (1990)
STL: A Seasonal-Trend Decomposition Procedure Based on Loess.
Journal of Official Statistics, 6, 3iV73.

## Examples

```
ts <- inzightts(visitorsQ)
d <- decomp(ts)
#> Decomp variable not specified, automatically selected `var = "Australia"`
if (FALSE) {
plot(d)
}
```