similar to: Using column length in plot gives error

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

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

Hello, I'm still a newbie user and struggling to automate some analyses from SigmaPlot using R. R is a great help for me so far! But the following problem makes me go nuts. I have two spectra, both have to be fitted to reference data. Problem: the both spectra are connected in some way: the stoichiometry of coefficients "cytf.v"/"cytb.v" is 1/2. {{In the SigmaPlot

Hi I'm fairly new to R and am trying to analyse some large spectral datasets using stepwise regression (fairly standard in this area). I have a field sampled dataset, of which a proportion has been held back for validation. I gather than step() needs to be fed a regression model and lm() can produce a multiple regression. I had thought something like: spectra.lm <-

Dear all, I work with (vibrational) spectra: some kind of intensity (I) over frequency (nu), wavelength or the like. I want to do fourier transform for interpolation, smoothing, etc. My problem is that the spectra are often irregularly spaced in nu: the difference between 2 neighbouring nu varies across the spectrum, and data points may be missing. Searching for discrete fourier transform

Hi there, I try to plot visible light spectrum (380nm~780nm) with color corresponding to the specific wavelength. However, I don't find a function that could do this. Another question, it's possible to plot a color space chromaticity diagram like this: http://upload.wikimedia.org/wikipedia/commons/thumb/0/02/CIExy1931.svg/300px-CIExy1931.svg.png Thanks in advance! Jinsong

Hi All. I'd like to generate a sample of n observations from a k dimensional multivariate normal distribution with a random correlation matrix. My solution: The lower (or upper) triangle of the correlation matrix has n.tri=(d/2)(d+1)-d entries. Take a uniform sample of n.tri possible correlations (runi(n.tr,-.99,.99) Populate a triangle of the matrix with the sampled correlations Mirror the

Dear list, I've recently become interested in comparing the spectral estimates using the different methods ("pgram" and "ar") in the spectrum() function in the stats package. With many thanks to the authors of these complicated functions, I would like to point out what looks to me like a bit of an inconsistency -- but I would not be surprised if there is good reasoning

Hi, I'm trying to obtain confidence intervals for auto and cross correlation estimates. I've adapted code made available by Stock and Watson that uses the Bartlett Kernel and the delta method. In R it runs really, really slow because of the loops it uses and I have 9 series that I'd like to examine (81 total combinations). It was easy enough to replace one of the while loops with a

Hello, I'm attempting to create a data frame with correlations between every pair of variables in a data frame, so that I can then sort by the value of the correlation coefficient and see which pairs of variables are most strongly correlated. The sm2vec function in the corpcor library works very nicely as shown here: library(Hmisc) library(corpcor) # Create example data x1 = runif(50) x2 =

Dear R users, I am trying to print heatmaps in a loop (with a pause). Idea is to visualize changing correlations over time and for testing I wrote this simple (reproducible) code below. My problem is that levelplot() does not produce any output when I run the code (though heatmap does). Ideally I would like to use levelplot() as it produces a neat index on the side indicating the color and the

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

Hi, I have some difficulty in figuring out whether I am doing correct or not. A brief introduction about the work: It is a light/dark choice test conducted in insect larvae.  The response is binary (0- present in dark area, 1-present in light area) and the experiment is run for 15 min, so there are 15 repeated measurements per individual larva at 1 min intervals.  The factors which affect

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

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:

First time ever that I try to call subroutines in a Win DLL using R. Have done this before using VBA and Python. The C code's function argument list contains only double pointers (double *x). The function is declared void, the output value is one of the arguments. C calling sequence is used. When inspecting the exports of the DLL with dumpbin I can see that the function I need is

Dear all, I wrote a wrapper to a FORTRAN program using R. The main program uses a text file (~200 lines) as an input describing the simulation to be run. I typically generate the file once with the right parameters using a combination of file(), paste(), cat(). This is fine, and it works well, however I then need to update only a few values in the file many times (~200 times,

I have a spectrophotometric dataset with repeated measures of a value at 200 wavelengths for each of 150 individuals. I would like to use the repeated samples to at each wavelength to look at measurement/observer error, compared to difference between individuals error I have looked at doing this with icc{irr} or using an anova approach, but I am unclear how to acheive this given that there

I would really appreciate it if someone can give suggestions on how to do spectra fitting in R using ordinary least square fitting and non-negativity constraints. The lm() function works well for ordinary least square fitting, but how to specify non-negativity constraints? It wouldn't make sense if the fitting coefficients coming out as negative in absorption spectra deconvolution. Thanks.

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