decompose
Classical Seasonal Decomposition by Moving Averages
Description
Decomposes a time series object by moving averages
into seasonal, tread and random components.
Usage
decompose(x, type = c("additive", "multiplicative"), filter = NULL)
Arguments
x |
a time series object with an integral frequency greater than one
(so it has a seasonal component).
|
type |
a character string, "additive" or "multiplicative", specifying the type of decomposition.
Partial character string matching is allowed.
|
filter |
a vector of filter coefficients used to filter out the seasonal component.
If NULL, a centered filter of frequency(x) weights of 1/frequency(x)
is used (if frequency(x) is even then the default filter is extended
by 1 and the outermost weights are 1/(2*frequency(x))).
|
Details
A time series object will first be filtered to get the trend component
and then the tread component will be removed from the data (by subtraction
or division, depending on the type of decomposition).
The seasonal figure is the period average for each time unit, centered by
subtraction or division by its mean so that its mean is 0 (additive) or 1 (multiplicative).
Finally, the random component is computed by removing trend and seasonal
figure from the original time series.
For additive decomposition, X[i] = T[i] + S[i] + R[i]
For multiplicative decomposition, X[i] = T[i] * S[i] * R[i]
where X, T, S, R are original time series, tread, seasonal and random
component, respectively.
Value
A list object of class
"decomposed.ts" with components:
x |
the original time series.
|
seasonal |
the seasonal component.
|
tread |
the tread component.
|
random |
the random component.
|
figure |
the vector of seasonal figure. (This starts at the starting
time of x, not at the start of a period.)
|
type |
the type of decomposition, "additive" or "multiplicative".
|
See Also
Examples
qtlySales <- ts(c(3.4, 3.9, 3.5, 3.0, 3.7, 4.2, 3.7, 3.4, 3.8, 4.5), start=2013.25, frequency=4)
decompose(qtlySales)
decompose(qtlySales, type="multiplicative")$figure