similar to: [LLVMdev] current llvm vs. current gcc code size

This is interesting. Nobody has tried very hard to get -Os to work well AFAIK, so it's that not surprising it doesn't:) Aside from optimization knobs, I don't think there's anything in x86 instruction selection to pick small code sequences, which can be important. I suspect -Os will become important later though. One thing that might be going on is differing default

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

Hello all, I have some histograms of amount of DNA in some cells (DU145 cells overexpressing Bax and Bcl-xL for those who wish to know). The histograms show not only two peaks as expected, but three, indicating that some cells have more than normal amounts of DNA. I am interested in knowing how much of the cell populations are in each peak as well as between. I am not really sure how to go

Hi All, I apologise if this question has been answered before, but my background is a little different from most people using R, and the language we use seems to be different! I am trying to analyse some nuclear physics data, which consists of an ensemble of "energy" readings in a detector that, when binned, form a number of Gaussian shaped peaks superimposed on a varying background

Hi all, I've tried to plot a vector which has two peaks in the density. This link shows the figure. http://docs.google.com/View?docid=dcvdrfrh_1dk9r2rc7 The red line is normal curve and green line is gamma curve. Notice that red line can correctly fit the histogram that has two peaks (i.e. red curve also has two peaks). But the gamma curve there only has one curve. Is there a way I can

This is probably a trivial question, but I did not see it in the FAQs. Perhaps I simply need to be pointed to some URLs. In any case, I have some sampled data that has peaks, and I would like to extract peak height, location, and width, according to almost any statistical model. Gaussian would seem to make the most sense. There can also be "steps" increasing the amplitude over a

In 2004 there was this R-Help posting from Jan 2004: http://finzi.psych.upenn.edu/R/Rhelp02a/archive/33097.html R equivalent of Splus peaks() function? The peaks function there has worked well for me on a couple of projects, but some code using "peaks" failed today, which had worked fine in the past. I was looking for a peak in a test case that was a sine curve over one

Hello, Thank you to all those great folks that have helped me in the past (especially Dennis Murphy). I have a new challenge. I often generate time-series data sets that look like the one below, with a variable ("Phase") which has a series of flat-topped peaks (sample data below with 5 "peaks"). I would like to calculate the phase value for each peak. It would be great to

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

http://r.789695.n4.nabble.com/file/n3312061/x_and_y_values.txt x_and_y_values.txt I have the absorbance values form HPLC Chromatogram. I need to find the peaks in datapoints and area under each peak. I am not sure how how to find the peaks, I tried couple of libraries and peak function but they return me a list of values which when computed from area turns out to be huge nnumbers. In the

I'm sure there must be various peak-finding algorithms out there. Not knowing of any, I have written one myself*, but I thought I'd ask to see what's out there. Basically, I have a 2-dimensional data set and I want to identify local peaks in the data, while ignoring "trivial" peaks. My naive algorithm first identifies every peak and valley (point of inflection change

Is there any R package that can help me with digging out the maxima of a 1-D trajectory ? I have 975 1-D curves. They are only known as time series. That is a set of points ordered with respect to time. Some curves exhibit one only peak. Others have two peaks of different height. We wish to find the number of peaks and their position along the time axis. Apparently it's a trivial problem

I've been asked in private, (and am replying BCC to the asker), >> I saw your post on the R-help archives page about the possibility of >> porting a function from S-Plus called peaks() to R. I am looking for >> some way to locate peaks in a simple x,y data set, and thought that R >> might be the way to go. "of course" it is the way to go, don't get

Hi everyone, first of all, I would like to say that I am a newbie in R, so I apologize in advance if my questions seem to be too easy for you. Well, I'm looking for periodicity in histograms. I have histograms of certain phenomenons and I'm asking whether a periodicity exists in these data. So, I make a periodogram with the function spec.pgram. For instance, if I have a histogram h, I

Hello all I'm trying to do a simulation that involves identifying the minimum point between two peaks of a (usually) bimodal distribution. I can do this easily if there are only two peaks: CnBdens<-density(Ys/Xs) #probability density function for ratio of Ys to Xs for(p in 1:512) ifelse(CnBdens$y[p]>CnBdens$y[p-1],peak1<-p,break) #identifies first peak in probability

So I have a problem that I'm trying to get through, and I just can't seem to get it to run very fast in R. What I'm trying to do is to find in a vector a local peak, then the next time that value is crossed later. I don't care about peaks that may be lower than this first one - they can be ignored. I've tried some sapply methods along the way, but they all are slower.

Hi I went through some extensive search to find suitable method (package, function) to fit multiple peaks. The best I found is ALS package but it requires rather complicated input structure probably resulting from GC-MS experimental data and seems to be an overkill to my problem. I have basically simple two column data frame with columns time and sig dput(temp) structure(list(time = c(33, 34,

Dear All, Does anybody know if there is a functionality in R to break histograms that show a clear bi-modal (or multi-modal) distribution into a series of unimodal histograms that added up result in the original histogram? I was thinking of using QQ-plots (for which tools are available in R), and then observing the number of times the observed quantiles cross the 1:1 line, but this only gives an

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 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