SigExtract: Signal Extraction And Optimal Filtering

In astsa: Applied Statistical Time Series Analysis

Signal Extraction And Optimal Filtering

Description

Performs signal extraction and optimal filtering as discussed in Chapter 4.

Usage

SigExtract(series, L = c(3, 3), M = 50, max.freq = 0.05, col = 4)

Arguments

series	univariate time series to be filtered
L	degree of smoothing (may be a vector); see spans in spec.pgram for more details
M	number of terms used in the lagged regression approximation
max.freq	truncation frequency, which must be larger than 1/M
col	color of the main graphs

Details

The basic function of the script, and the default setting, is to remove frequencies above 1/20 (and, in particular, the seasonal frequency of 1 cycle every 12 time points). The sampling frequency of the time series is set to unity prior to the analysis.

Value

Returns plots of (1) the original and filtered series, (2) the estiamted spectra of each series, (3) the filter coefficients and the desired and attained frequency response function. The filtered series is returned invisibly.

Note

The script is based on code that was contributed by Professor Doug Wiens, Department of Mathematical and Statistical Sciences, University of Alberta.

Author(s)

D.S. Stoffer

References

You can find demonstrations of astsa capabilities at FUN WITH ASTSA.

The most recent version of the package can be found at https://github.com/nickpoison/astsa/.

In addition, the News and ChangeLog files are at https://github.com/nickpoison/astsa/blob/master/NEWS.md.

The webpages for the texts and some help on using R for time series analysis can be found at https://nickpoison.github.io/.

astsa documentation built on May 29, 2024, 10:29 a.m.