How to Run a High Pass or Low Pass Filter on Data Points in R

How do I run a high pass or low pass filter on data points in R?

Per request of OP:

The signal package contains all kinds of filters for signal processing. Most of it is comparable to / compatible with the signal processing functions in Matlab/Octave.

Using lanczos low pass filter in R program

Using the web I find this MATLAB implementation.

If you skipped the first part(arguments check), it looks simple to write its R equivalent.

#      Cf   - Cut-off frequency       (default: half Nyquist)
#      M    - Number of coefficients  (default: 100)
lanczos_filter_coef <- function(Cf,M=100){
  lowpass_cosine_filter_coef <- function(Cf,M)
    coef <- Cf*c(1,sin(pi*seq(M)*Cf)/(pi*seq(M)*Cf))
  hkcs <- lowpass_cosine_filter_coef(Cf,M)
  sigma <- c(1,sin(pi*seq(M)/M)/(pi*seq(M)/M))
  hkB <- hkcs*sigma
  hkA <- -hkB
  hkA[1] <- hkA[1]+1
  coef <- cbind(hkB, hkA)
  coef
}

To test it for example:

dT <- 1
Nf <- 1/(2*dT)
Cf <- Nf/2
Cf <- Cf/Nf
lanczos_filter_coef(Cf,5)

               hkB           hkA
[1,]  5.000000e-01  5.000000e-01
[2,]  2.977755e-01 -2.977755e-01
[3,]  1.475072e-17 -1.475072e-17
[4,] -5.353454e-02  5.353454e-02
[5,] -4.558222e-18  4.558222e-18
[6,]  2.481571e-18 -2.481571e-18

PS I don't know very well MATLAB(used it many years ago), so I I used this link For the R/MATLAB analogy. I hope that someone with more R/MATLAB/Scilab knowledge can test my code.

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