Applying Savitzky-Golay filters in “R”

[This article was first published on NIR-Quimiometría, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

When applying SG, we select a moving average window with an odd value “n” for the number of data points. SG fit a polynomial of “p” degree to this data points and give the value to the central point (this is the reason to have an odd value).
We apply also an smooth in the case of “m” = 0, or the first (m=1), second (m=2) or third (m=3) derivatives.

Apply a Savitzky-Golay smoothing filter
Description
Smooth data with a Savitzky-Golay smoothing filter.
Usage
sgolayfilt(x, p = 3, n = p + 3 – p%%2, m = 0, ts = 1)
## S3 method for class ‘sgolayFilter’
filter(filt, x, …)
Arguments

x
signal to be filtered.
p
filter order.
n
filter length (must be odd).
m
return the m-th derivative of the filter coefficients.
ts
time scaling factor.
filt
filter characteristics (normally generated by sgolay).


Playing with these three parameter we change the shape of the spectra.

Example:
The upper spectra was taken with p=2, n=7 and m=2
The lower one with p=2, n=31 and m=2
As we can see the size of the window has a big influence on the resolution of the peaks.
How to apply it in R:
(For the lower spectrum)
>sgolay_2_31_2<-apply(fattyac$NITm,1,sgolayfilt,p=2,n=31,m=2)
>matplot(wavelengths,sgolay_2_31_2,lty=1,pch=21,
 + xlab=”nm”,ylab=”SG_2_31_2_abs”)


To leave a comment for the author, please follow the link and comment on their blog: NIR-Quimiometría.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)