hamilton_filter {deseats} | R Documentation |
Time Series Filtering Using the Hamilton Filter
Description
A stationary remainder is obtained from a univariate time series using the filter proposed by Hamilton. The filter is capable of estimating the trend together with the seasonality in a series.
Usage
hamilton_filter(yt, h = NULL, p = NULL)
Arguments
yt |
a time series object of class |
h |
the backwards time skip for the first regressor; the default is
the seasonal period in |
p |
the number of regressors; the default is the seasonal period in
|
Details
Implement the filter by Hamilton (2018) to decompose a time series.
Value
A list with the following elements is returned.
- decomp
an object of class
"mts"
that consists of the decomposed time series data.- ts_name
the object name of the initially provided time series object.
- frequency
the frequency of the time series.
- regression_output
an object of class
"lm"
, i.e. basic regression output.
References
Hamilton, J. D. (2018). Why You Should Never Use the Hodrick-Prescott Filter. The Review of Economics and Statistics, 100(5): 831–843. DOI: 10.1162/rest_a_00706.
Examples
est <- hamilton_filter(log(EXPENDITURES))
est