similar to: least square fit with non-negativity constraints for absorption spectra fitting

Dear useRs, I have a curve which is a mixture of Gaussian curves (for example UV emission or absorption spectrum). Do you have any suggestions how to implement searching for optimal set of Gaussian peaks to fit the curve? I know that it is very complex problem, but maybe it is a possibility to do it? First supposement is to use a nls() with very large functions, and compare AIC value, but it is

Hi, I'm trying to match peaks between chromatographic runs. I'm able to match peaks when they are chromatographed with the same method, but not when there are different methods are used and spectra comes in to play. While searching I found the ALS package which should be usefull for my application, but I couldn't figure it out. I made some dummy chroms with R, which mimic my actual

Hello, Has anyone written R functions for applying self-controlled case series methods (http://statistics.open.ac.uk/sccs/). In fact only thing needed is to modify glm function to allow absorption of effect. Eg. in Poisson model individual effect is used as factor, but it is considered as nuisance term where parameter estimates are not needed. Could anyone point how absorbing individual

Hi all, I need to insert the name of spectra in a stacked plot obtained with hyperspec. I use this command plot(spectra [c(-1:-4, -6:-8, -10:-12, -14:-16)], stacked = T) but, in this way R draw nameless spectra on the Y axis. How can I solve the problem? Thank you for any suggestion. Best regards, Roberto -- View this message in context:

Hi Folks... No code to troubleshoot here. I need some suggestions about the right terminology to use in further searching, and any suggestions about R pkgs that might be appropriate. I am in the planning stages of a project in which IR, NMR and other spectra (I'm a chemist) would be collected on various samples, and individual samples would be followed over time. The spectra will be feature

Dear all, This is potentially a bug in spec.pgram, when the number of samples is odd,spec.pgramreturns a different result withfast = TRUE, the example below contains the two varieties with a reference spectrum calculated manually. the number of returned spectra is also larger (50 compared to 49) whenfast = TRUE x <- rnorm( 99 ) plot(spec.pgram(x, taper = 0 , detrend = FALSE , plot =

+ llvm-dev From: Sumner, Brian Sent: Tuesday, May 10, 2016 3:11 PM To: Anastasia Stulova <Anastasia.Stulova at arm.com>; Liu, Yaxun (Sam) <Yaxun.Liu at amd.com>; cfe-dev (cfe-dev at lists.llvm.org) <cfe-dev at lists.llvm.org>; Pan, Xiuli <xiuli.pan at intel.com>; Bader, Alexey (alexey.bader at intel.com) <alexey.bader at intel.com> Cc: Stellard, Thomas

Dear collegues, I´ ve worked with near infrared (NIR) spectroscopy to assess chemical, physical, mechanical and anatomical properties of wood. I use "The Unscrambler" software to correlate the matrix of dependent variables (Y) with the matrix of spectral data (X) and I would like to migrate to R. The matrix of spectral variables is very large (2345 columns and n lines, where n =

I want to run deconvolution of a time series by an impulse or point-spread function through Wiener filter, regularized filter, Lucy-Richardson method, or any other approaches. I searched the CRAN website and the mailing list archive, but could not find any package for such a deconvolution analysis. Does anybody know an existing R function for deconvolution? TIA, Gang

Hello, We are now facing a bug caused by the GVN pass, only part of the code was optimized. I have found that the problem is cause by an Limit in lib/Analysis/MemoryDependenceAnalysis.cpp 00055 static cl::opt<unsigned> BlockScanLimit( 00056 "memdep-block-scan-limit", cl::Hidden, cl::init(100), 00057 cl::desc("The number of instructions to scan in a block in

Hello list! I would like to fit a distribution to each of the peaks in a histogram, such as this: http://photos1.blogger.com/blogger/7029/2724/1600/DU145-Bax3-Bcl-xL.png . The peaks are identified using Petr Pikal peaks function ( http://finzi.psych.upenn.edu/R/Rhelp02a/archive/33097.html), but after that I am quite stuck. Any idea as to how I can: Fit a distribution to each peak Integrate the

I need to extract the p value from a ANOVA done with lm model fitting <- lm(var ~ group) Sfitting <- summary(fitting) Sfitting[10][1] gives the F value and the degrees of freedom but I am not able to get the p value. The function df should give a p value given a F but I am not able to make it work. I found only something about aov in the R help and I am not able to make it work Massimo

Hi all, I'll have to filter Raman spectra and I would like to do so in R. I'm trying to figure out how. Maybe one of you could help me ... This is what I have to do: General: separate the real spectrum (the set of peaks) from two contaminations: a drifting background and (white) noise Constraints (which should help the task): A - the spectrum is positive B - the spectrum is long

look at the spectrums before you do the cbind - I would not suggest letting R wrap the data to fill in a data frame. I would suggest using something that you "know how it acts" in the frequency domain like zero. You are probably introducing periodicies that are not real, and I would suggest not to go down this path. As for finding commonalities amongst signals- it all depends on what

Hi Everyone- After searching through posts and my favorite R-help websites I'm still confused about a problem. I have data which is bimodal in nature, but there is no clearly obvious separation between the two peaks. In programs such as Origin, I can deconvolute the two distributions and have it generate a "best guess" as to what the two subpopulations are which make up my

Dear R users, I am a newbie. Just switched from MATLAB. So thanks a lot for your patience. I have 50000 spectra collected in field. Each spectra has two columns : Wavelength (56) and the actual measurement. Each measurement came in a different .txt file on disk (50000 files in total). I wrote a script that reads every spectra in a for loop and constructs two variables : Wavelength (56) and

Thanks. Eric Leifer, Ph.D. Office of Biostatistics Research National Heart, Lung, and Blood Institute 6701 Rockledge Drive, MSC 8217 Bethesda, MD 20892-8217 Email: LeiferE@NHLBI.NIH.GOV Phone: 301-435-0436 FAX: 301-480-1862

Hi I'm trying to write a generic script for processing some data which finishes off with some plots. Given Im never sure how many columns will be in my dataframe I wanted to using the following plot(spectra.wavelength, cormat, type = "l", ylim=c(-1,1), xlab="Wavelength (nm)", ylab="Correlation") however even if I specify as type="l" it appears plot

Hi, I am currently analysis Raman spectroscopic data with the hyperSpec package. I consulted the documentation on this package and I found an example work-flow dedicated to Raman spectroscopy (see the address : http://hyperspec.r-forge.r-project.org/chondro.pdf) I am currently trying to remove outliers thanks to PCA just as they did in the documentation, but I get a message error I can't

Hi, I have a data frame Y with the following information, ORF spectra 1 YAL001C 2 2 YAL005C 21 3 YAL007C 2 4 YAL012W 8 5 YAL016W 24 6 YAL019W 3 7 YAL020C 2 8 YAL021C 7 9 YAL022C 3 10 YAL023C 6 11 YAL026C 2 12 YAL029C 1 13 YAL031C 1 14 YAL035W 48 15 YAL038W 173 16 YAL041W 4 17 YAL042W 4 18