I'm adapting MATLAB code to R and trying to generate a waveform using ARMA formula. Is there a simple R equivalent function for MATLAB's filter
to take AR/MA coefficients to build a waveform?
npts = 100;
a = [1 0.6]; % AR coeffs
b = [1 0.25 3]; % MA coeffs
e = randn(npts,1); % generate gaussian white noise
waveform = filter(b,a,e); % generate waveform
Filters are data processing techniques that can smooth out high-frequency fluctuations in data or remove periodic trends of a specific frequency from data. In MATLAB®, the filter function filters a vector of data x according to the following difference equation, which describes a tapped delay-line filter.
na is the feedback filter order, and nb is the feedforward filter order. Due to normalization, assume a(1) = 1. You also can express the rational transfer function as the difference equation. a ( 1 ) y ( n ) = b ( 1 ) x ( n ) + b ( 2 ) x ( n − 1 ) + ... + b ( n b + 1 ) x ( n − n b ) − a ( 2 ) y ( n − 1 ) − ...
Lowpass Filtering of Tonesfs = 1e3; t = 0:1/fs:1; x = [1 2]*sin(2*pi*[50 250]'. *t) + randn(size(t))/10; Lowpass-filter the signal to remove the high-frequency tone. Specify a passband frequency of 150 Hz.
Yeah, you can do this usring arima.sim
, e.g.
arima.sim(npts, model=list(ar=a, ma=b), rand.gen=rnorm)
Note that the model is checked for stationarity and the model you have above is not stationary. If you want something integrated you can specify the order of integration in the model.
Hmm can't you achieve that with filter
function in the package signal ?
require(signal)
a = c(1,0.6)
b = c(1,0.25,3)
e = rnorm(100)
waveform = filter(b,a,e)
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