similar to: Applying a function to an array

Hello, I am a newcomer to R and therefore apologize for posting such a basic question. I am trying to multiply 2 matrices t(X1)%*%X1, where t(X1) is: 1 2 3 4 5 8 12 13 20 24 26 27 31 33 34 36 37 40 41 42 45 46 47 48 49 ones 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Shadow 0 1 1 1 1 1 1 1 0 1 1 1 1 0 1 0

Dear R experts, How to find out the index of minimum or maxmum number in a vetor or data.frame? For example, a= n price 1 50 -2 100 0 200 -1 300 ...... I want to find out the row which the n is the smallest or largestest and extract the price. Thanks Ted -- View this message in context:

I'm trying to create a graph where different cells of a grid (a shapefile) will be painted with a color share scale, where the most easy way is to use gray(). Can I somehow get a vector (gradient) of colors, a vector of colors with other methods but gray()? I'm doing this until now quad_N_sp <-

Dear useRs, With the rise of netbooks and 'lifestyle laptops" I am tempted to get one of these to mainly run R on it. Processor power and hard disk space seem to be ok. What I wonder is the handling and feel with respect to R. Has anyone here installed or is running R on one of these, and if so, what is your experience? Would it be more of a nice looking gadget than a feasable platform

Thanks, I tried someting like this, but computation takes times for large matrices btransf <- function(y,X=length(y)^4) { N <- length(y) bm <- matrix(rep(1/N,N^2),N,N) for(j in 1:X){ coord <- sample(1:N,4,replace=T) d <- runif(1,0,min(bm[coord[1],coord[2]],bm[coord[3],coord[4]]))

Maybe I do not explain well what I would like to do. I do not want to change the labels of the axis, but the scale. What I want is a general procedure for changing the scale. Its like using a logarithmic scale on a plot. Labels are the same, but the increases of x along the x-axis are defined by a known monotone and continuous function. Florent Bresson ----- Message d'origine ---- De :

This is some interesting: > -8^(1/3) [1] -2 > x=(-8:8) > y=x^(1/3) > y [1] NaN NaN NaN NaN NaN NaN NaN NaN 0.000000 1.000000 [11] 1.259921 1.442250 1.587401 1.709976 1.817121 1.912931 2.000000 So, can anybody explain this?! (Why is x[1]^(1/3)=y[1]=NaN, but -8^(1/3)=-2?) Thx!!! [[alternative HTML version deleted]]

deaRs, I want to build a covariance matrix out of the data from a binary file, that I can read in chunk by chunk, with each chunk containing a single observation vector X. I wonder how to do that most efficiently, avoiding the calculation of the full symmetric matrices XX'. The trivial non-optimal approach boils down to something like: Q <- matrix(rnorm(100000),ncol=200) M <-

I am pretty new to R. So this may be an easy question for most of you. ? I would like to calculate the squared distances of a large set (let's say 20000) of vectors (let's say dimension of 5) to a fixed vector. ? Say I have a data frame MY_VECTORS with 20000 rows and 5 columns, and one 5x1 vector y. I would like to efficiently calculate the squared distances?between each of the 20000

Yes, you're right. In fact, it's just an adaptation of a matlab command and the author advises using N^4 replications that's why it's the default in the function. The bistochastic matrix is not my subject of interest, but I need it to perform some random tranformation of a vector of incomes. Florent Bresson ----- Message d'origine ---- De : Richard M. Heiberger <rmh at

I have to estimate the following model for several group of observations : y(1-y) = p[1]*(x^2-y) + p[2]*y*(x-1) + p[3]*(x-y) with constraints : p[1]+p[3] >= 1 p[1]+p[2]+p[3]+1 >= 0 p[3] >= 0 I use the following code : func <- sum((y(1-y) - p[1]*(x^2-y) + p[2]*y*(x-1) + p[3]*(x-y))^2) estim <- optim( c(1,0,0),func, method="L-BFGS-B" , lower=c(1-p[3], -p[1]-p[3]-1,

Hi, I am trying to plot several columns in different graphs in columns and rows. The first column of my data file is the time, and the third is the 'elevation angle' with 19 different numbers. I would like to plot the rest of the columns with the x axis as time and the individual angles in different colours. Here is the code I am using right now. It plots the different columns with time,

I have defined a function to compute the value of a beta distribution of the second kind (the existing beta distribution of th stats package is the beta distribution of the first kind). It works perfectly for a single value, but I want to apply it to a vector of 22 000 values. I can use a loop for the calculation of each value but it runs very very slowly. So, what can I change ? Hers's the

I have to calculate some formula like: gamma(x)/(gamma(x+y) and I observed that for relatively big values of x, R returns infinity and so cannot compute the formula. Is it possible to force R to give the real value of gamma(x) instead of Inf ? thanks

Please, I would like to generate a random bistochastic matrix, that is a squared matrix of non-negative numbers with each row and each column sum to 1, for example : .2 .3 .5 .6 .3 .1 .2 .4 .4 I don't know of to code this. Do you have any idea ? Thanks Florent Bresson ___________________________________________________________________________ Demandez ?

Hi, I'm trying to set the minimum and maximum in a parallel plot, but trying xlim=c(-1,1) gives strange results. Am I missing something? The call I give is: parallel(~X[,c(6,9,12,15,18)]|X$ff,X,panel=panel.parallel.new,groups=X$protein,layout=c(3,1),xlim=c(-1,1)) Besides, I would like to add a reference line to the plot, but can't find how to do that. I hope someone can give me a

Dear all, I have a large matrix with about 2500 variables, and 100 rows. I would like to calculate the means of the every 10 variables starting from 1:2500 and saving the results as a vector or matrix. How can I do that? Alternatively, How can I create 250 subset matrices in the order of variables 1:2500 in groups of 10 from the single matrix which had initially 2500 variables ? I guess I have

Hello R-helpers, I am trying to search for string that includes the caret symbol, using the following code: grepl("latitude^2",temp) And R doesn't like that. It gives me: > temp<-c("latitude^2","latitude and latitude^2","longitude^2","longitude and longitude^2") > temp [1] "latitude^2" "latitude and

I' m trying to compute weighted mean on different groups but it only returns NA. If I use the following data.frame truc: x y w 1 1 1 1 2 2 1 3 1 1 4 2 0 2 1 0 3 2 0 4 1 0 5 1 where x is a factor, and then use the command : tapply(truc$y,list(truc$x),wtd.mean, weights=truc$w) I just get NA. What's the problem ? What can I do ?

Hello! I'm trying to build a lower triangular matrix (with zeros in the diagonal) from a particular dataframe. The matrix I have to construct has 203 rows and 203 columns and that makes 20503 values to be included within (that's why I can't do it manually). To illustrate the dataframe I have, I'll give you an example of a dataframe and matrix with dimensions 6x6 (to make it