similar to: peaks

If there something available in R that has the functionality of the S-PLUS peaks() function? Thanks, Mirka

I would like to import "tif" images in R and I do not find any function that can do that. In Matlab there exists the function "imread" that can read the most known images format. Does a similar function exist for R ? Thanks in advance -- Herve CARDOT ____________________________________________________________ Unite Biometrie et Intelligence Artificielle, INRA Toulouse BP

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

Full_Name: Benny van der Vijgh Version: 2.7.2 OS: Windows Vista Submission from: (NULL) (194.171.252.108) The return value of peaks() in package splus2R is not consistent. This is because of the call to max.col() without additional parameters which peaks() makes. max.col() has a parameter 'ties.method' which specifies how ties are handled, with "random" by default. This means

Running R.app on Mac OS X 10.4 > version _ platform powerpc-apple-darwin8.6.0 arch powerpc os darwin8.6.0 system powerpc, darwin8.6.0 status major 2 minor 3.1 year 2006

Running R.app on Mac OS X 10.4 > version _ platform powerpc-apple-darwin8.6.0 arch powerpc os darwin8.6.0 system powerpc, darwin8.6.0 status major 2 minor 3.1 year 2006

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

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, I apologize for not following the posting rules? Here is the text from my previous post: "I started evaluating the 'Peaks' package a couple of months ago and found it to be quite useful. Getting back to it last week I had to set up my R environment due to hardware changes again. The Peaks package loads with no problem. After successfully reinstalling all packages (RedHat

I installed the locfit package under Linux (gcc 2.7.2). Installation was ok but > x <- runif(200) > y.compl <- 10*x*x*rgamma(200,3) > med.y <- median(y.compl) > cens <- ifelse(y.compl<=med.y,1,0) > y <- cens * y.compl + (1-cens)*med.y > library(locfit) > m <- locfit(y~x,cens=cens,family="gamma") /usr/local/src/R-0.61.1/bin/R.binary: can't

Greetings all, I am using Fourier analysis to search for periodicities in IP network traffic by generating periodograms and then visually examining them for large, distinct peaks. However, in many cases it is not readily apparent where there are periodicities. I have no experience with discrete maths so I've come up against a block here: How do I define what the "noise floor"

Dear useRs and wizaRds, I am currently developing a set of functions using S4 classes. On the way I encountered the problem exemplified with the code below. For some reason the 'validity' method does not seem to work, i.e. does not check for errors in the specification of the slots of the defined class. Any hints? My understanding of the whole S4 system was that validity checks are made

This is a simple SSA code generation 101 question. If I follow the IR code generation techniques in the Dragon book the statement x = y + z would translate into something like this in SSA/LLVM %0 = add %y, %z %x = %0 Obviously "copy instructions" like %foo = %bar are senseless in SSA since %foo and %bar are immutably fixed to the same value and there is no need for two aliases

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

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

Hello, it wanted to know how I can extract of a dates frame the values peaks according to an interval that I establish. For example if dates are: 1 23 2 4 3 56 4 7 5 99 6 33 extract the date i wanted to divide into intervals of 2 an d to take alone the numbers 23, 56 and 99 of those 3 intervals. Thanks Ruben

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

Would introducing the new frame, with the call to local(), cause problems when you use frame counting instead of <<- to modify variables outside the scope of lapply's FUN, I think the frame counts may have to change. E.g., here is code from actuar::simul() that might be affected: x <- unlist(lapply(nodes[[i]], seq)) lapply(nodes[(i + 1):(nlevels - 1)],

From: Daniel Kaschek <daniel.kaschek at physik.uni-freiburg.de> > ... When I evaluate this list of functions by > another lapply/sapply, I get an unexpected result: all values coincide. > However, when I uncomment the print(), it works as expected. Is this a > bug or a feature? > > conditions <- 1:4 > test <- lapply(conditions, function(mycondition){ >

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