similar to: matlab norm(h) command in R: sqrt(sum(h^2)) - use in an expression

> From: Christoph Lehmann > > Hi > > in matlab I defined a function (double gamma, parameters at > the end of > this mail) as > h(i)=((t/d1)^a1)*exp(-(t-d1)/b1)-c*((t/d2)^a2)*exp(-(t-d2)/b2); > h=h/norm(h); > > I do know that norm() in matlab is equal to: > > sqrt(sum(x^2)) > in R > so in R I do it like: > > #function (double

Hi Elisa, I hope this is what you wanted. dat1<-read.csv("peaks.csv",sep=",") #Subset dat2<-dat1[1:5,] res1<-do.call(cbind,lapply(seq_len(nrow(dat2)),function(i) do.call(rbind,lapply(split(rbind(dat2[i,],dat2[-i,]),1:nrow(rbind(dat2[i,],dat2[-i,]))), function(x) {x1<-rbind(dat2[i,],x);

Hello, I need to calculate the correlation for all pairwise combinations in a very large matrix. I have 25,000 elements and need to calculate the pairwise correlation with a different set of 5,000 elements. I have written code that works, but it is extremely slow. At the current rate, it will take a few weeks to finish running. I'm looking for suggestions on performing the calculations

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

I need to find a way how to execute an expression with the new command line parameter in R (R -e "AnExpression") without R get closed after the expression has been evaluated. For example if i want to start R with a plot or start R with a *.RData file. Any help or suggestions are appreciated ! -- View this message in context:

Hey eveyone! I hope someone can help wiht this question. I have a matirux of all zeros and ones and I would like to indentify all unique patterns in the rows andthe number of times the pattern occurs. I changed all zeros to NA tried to use prelim.norm to identify all patterns of missing data in the rows. I got the message Warning message: NAs introduced by coercion Any ideas of how

dear list members, there seems to be a problem with the prelim.norm function (package norm) as number of items in the dataset increases. the output of prelim.norm() is a list with different summary statistics, one of them is the missingness indicator matrix "r". it lists all patterns of missing data and a count of how often each pattern occured in the dataset. as the number of items and

I am conducting a simulation study generating multivariate normal data, deleting observations to create a data set with missing values and then using multiple imputation via da.norm in Schafer's norm package. >From da.norm, I get the following error message: "Error: NA/NaN/Inf in foreign function call (arg 2)" The frequency of the error message seems to depend on the ratio of n

Hello all I'm running da.norm function in R for climate data rngseed(1234567) theta1=da.norm(mydata, thetahat, steps=1000,showits=T) param1=getparam.norm(mydata,theta1) As I understand the 1000 steps represent the markov chain values. Is there a way to plot them? Something like plot(1:1000, param1$mu[]). I just can't find a way to extract them out of my theta1. Thank you, Andrey.

Hello and apologies if this is a stupid question (just rejoined the list): Has anything changed with the norm() function with the latest update of the Matrix library? My old code seems not to be working properly even for very simple tests of the norm function. I get too many "No direct or inherited method for function "norm" for this call" messages. I am using windows, R

Hello, i need some help concerning the library norm. i habe to impute some missing values using the em algorithm. The help offered for the library doesn't really help me, maybe somebody already worked on em algorithm or multiple imputation. some fictive Data x1 x2 50 60 24 . 26 20 87 . 21 . Problem: Em Algorithm in R calculating the missings in x2. Thanks in advance. -- View this

Dear All, Thanks a lot for this quick help. I've managed to solve the issue. The problem was that I haven't installed the readline-devel and ncurse-devel packages. It compiled nicely Cheers, Antonio ---

Hi all Just wondering whether one can undertake Lp norm estimation (a type of regression analysis) in R? i.e. argmin S ( | y(i) - x(i)b | ^p ) where: * S is the summation over observation i= 1,2,...,n * y is a vector of n observations * x is an n by p matrix of explanatory variables * b is a p by 1 vector of beta coefficients and * p is a constant to be estimated such that

Hi! I want o calc the norm of a complex number ( |c| where c is complex). Does the function abs() this ? Thanks, -- Frank G. Zoellner AG Angewandte Informatik Technische Fakult"at Universit"at Bielefeld phone: +49(0)521-106-2951 fax: +49(0)521-106-2992 email: fzoellne at techfak.uni-bielefeld.de

Hi everyone, I'm trying to use prelim.norm with a "big" matrix (36 columns by 10000 or so rows). I found that prelim.norm has a built-in limit of 30 columns, but I'd still really like to use it for my data. Does anyone know of a different way to do the same thing? Or, would it be easier to try to modify the source code? Thanks! Josh

Hello everyone, I am looking into time series data compression at the moment. The idea is to fit a curve on a time series of n points so that the maximum deviation on any of the points is not greater than a given threshold. In other words, none of the values that the curve takes at the points where the time series is defined, should be "further away" than a certain threshold from the

Dear all, Is anybody knows simple method for creation norm tables for psychological tests for several groups distinguished by sex and age? best regards, Krzysztof

Dear all, I have been implementing some bootstrap-related methods, and came across this theoretically undesirable behaviour in the computation of bootstrap quantiles. The manual says: ?Interpolation on the normal quantile scale is used when a non-integer order statistic is required.? Theoretically, when R=999 and (R+1)*alpha is integer, then, the calculations of the 95% CI should never contain

I'm trying to use either mice or norm to perform multiple imputation to fill in some missing values in my data. The data has some missing values because of a chemical detection limit (so they are left censored). I'd like to use MI because I have several variables that are highly correlated. In SAS's proc MI, there is an option with which you can limit the imputed values that are

On Nov 11, 2013, at 10:44 PM, Hal Finkel <hfinkel at anl.gov> wrote: >> "Unlike sqrt in libm, however, llvm.sqrt has undefined behavior for >> ..." >> >> to "... produces an undefined value", with a link back to >> ##undefined-values. > > I'm not sure that helps, because it will prevents sqrt + -fno-math-errno (a readnone sqrt)