| filter {signal} | R Documentation |
Filter a signal
Description
Generic filtering function. The default is to filter with an ARMA filter of given coefficients. The default filtering operation follows Matlab/Octave conventions.
Usage
## Default S3 method:
filter(filt, a, x, init, init.x, init.y, ...)
## S3 method for class 'Arma'
filter(filt, x, ...)
## S3 method for class 'Ma'
filter(filt, x, ...)
## S3 method for class 'Zpg'
filter(filt, x, ...)
Arguments
filt |
For the default case, the moving-average coefficients of
an ARMA filter (normally called ‘b’). Generically, |
a |
the autoregressive (recursive) coefficients of an ARMA filter. |
x |
the input signal to be filtered. |
init, init.x, init.y
init, init.x, init.y |
allows to supply initial data for the filter - this allows to filter very large timeseries in pieces. |
... |
additional arguments (ignored). |
Details
The default filter is an ARMA filter defined as:
a_1y_n + a_2y_{n-1} + \dots + a_ny_1 = b_1x_n +
b_2x_{m-1} + \dots + b_mx_1
The default filter calls stats:::filter, so it returns a
time-series object.
Since filter is generic, it can be extended to call other filter types.
Value
The filtered signal, normally of the same length of the input signal x.
Author(s)
Tom Short, EPRI Solutions, Inc., (tshort@eprisolutions.com)
References
https://en.wikipedia.org/wiki/Digital_filter
Octave Forge https://octave.sourceforge.io/
See Also
filter in the stats package, Arma,
fftfilt, filtfilt, and runmed.
Examples
bf <- butter(3, 0.1) # 10 Hz low-pass filter
t <- seq(0, 1, len = 100) # 1 second sample
x <- sin(2*pi*t*2.3) + 0.25*rnorm(length(t)) # 2.3 Hz sinusoid+noise
z <- filter(bf, x) # apply filter
plot(t, x, type = "l")
lines(t, z, col = "red")