search for: mats

I ran into a problem with "subset" while working at home that I am not sure is a bug or not. I defined a custom function to take a data frame of tree positions, sizes, and types (containing the columns TRT, COMP, PLOT, X, Y, DBH and CON) and wanted to make a stem map of the plot using different symbols and colors to represent the different types of tree stems. I copied a bit of the

> > I am looking for a more elegant way to write below code. > > #Simulation results have different dimensions > mysim <- lapply(1:10, function(y) { > two.mat <- matrix(rnorm(4), nrow = 2) > four.mat <- matrix(rnorm(16), nrow = 4) > list(two.mat = two.mat, four.mat = four.mat) #results with different dimensions > }) > > #Collect different

I would use replicate() to do an operation with random numbers repeatedly: ``` mysim <- replicate(10, { two.mat <- matrix(rnorm(4), 2, 2) four.mat <- matrix(rnorm(16), 4, 4) list(two.mat = two.mat, four.mat = four.mat) }) ``` which should give you a matrix-list. You can slice this matrix-list just like normal, then cbind it in one step: ``` two.mat <-

Hola tengo una tabla de tipo data.frame "datos" con la siguiente estructura, simplificada en número de niveles por variable, para crear un ejemplo más sencillo: id anio t_8a t_10a t_12a rankf8 rankf10 rankf12 1 1 100 220 220 NA NA NA 2 1 140 350 350 NA NA NA 3 2 55 165 165 NA NA NA 4 2 60 200 200 NA NA NA 5 2 100 NA NA NA NA NA 6 3 NA 350 350 NA NA NA También tengo una matriz,

Dear community, I had been looking for an easy way to produce latex tables from R output. xtable() and the package apsrtable produce good outputs but they are not exactly what I was looking for. I wrote this code that generates regression tables from multiple R linear models. I want to share it because it might be useful for someone else, and because I would appreciate comments on how to

I am trying to calculate the weighted mean for a of 10 deciles and I get an error: > decile <- tapply(X=mat$trt1m, INDEX=mat$Rank, FUN=weighted.mean, w=mat$mcap) Error in FUN(X[[1]], ...) : 'x' and 'w' must have the same length All three of my inputs have the same length, as shown below, and the weighted.mean calculation works by itself, just not in tapply() >

HI, I am really messing up to make a symmetrical matrix using upper.tri() & lower.tri() function. Here is my code:   > set.seed(1) > mat = matrix(rnorm(25), 5, 5) > mat            [,1]       [,2]       [,3]        [,4]        [,5] [1,] -0.6264538 -0.8204684  1.5117812 -0.04493361  0.91897737 [2,]  0.1836433  0.4874291  0.3898432 -0.01619026  0.78213630 [3,] -0.8356286  0.7383247

Error in model.frame When I run the following nls model an error message appears and I dont know how to solve that. Could you help me?? mat = c(1,2,3,4,5,6,7,8,9,12,16,24,36,48,60) for (i in 1:length(j30)) { bliss = nls(c(j[i,1:length(mat)]) ~ b0 + b1*((1-exp(-k1*mat))/(k1*mat)) + b2*(((1-exp(-k2*mat))/(k2*mat))-exp(-k2*mat)), start = list(k1=0.1993, k2=0.1993, b0= 22.0046,

Hi!! I am trying to multiply 5 matrices and then using the inverse of that matrix for further computation. I read about precision problems from the archives and the suggestion was to use as.numeric while computing the products. I am still having problems with the results. Here is how I am using it #Mn.mat<-(T.mat %*% Rz.mat %*% Q.mat %*% Rz.mat %*% T.mat) # I was doing this in one step

Dear all, I have a problem with the "subset()" function. I spent all day yesterday with a collegue to solve it and we did not find a satisfying solution (even in the archived mails), so I ask for your help. Let's say (for a simple example) a matrix mat: R> mat cola colb colc [1,] 1 4 7 [2,] 2 5 8 [3,] 3 6 9 My goal is to select the lines of the matrix on the basis of the

Hi everyone, I posted something similar to this in reply to another post, but there seems to be a problem getting it onto the board, so I'm starting a new post. I am trying to use conditional formatting to select non-zero and non-NaN values from a matrix and pass them into another matrix. The problem is that I keep encountering an error message indicating the ":missing value where

Dear R-community, my data set looks like 'mat' below. Plant<-c(NA,1,1,1,NA,NA,NA,NA,NA,1); Value1<-rnorm(1:10); Value2<-rnorm(1:10); mat<-cbind(Plant,Value1,Value2); I receive data from two different sites. One site is identified by an interger number, the other site has no data in column Plant=NA. My pb: I'm trying to assign labels "A" or "B" to

List: Thank you for the replies to my post yesterday. Gabor and Phil also gave useful replies on how to improve the function by relying on mapply rather than the explicit for loop. In general, I try and use the family of apply functions rather than the looping constructs such as for, while etc as a matter of practice. However, it seems the mapply function in this case is slower (in terms of CPU

I have a matrix and am trying to write a code to 1. identify all neg values along each line 2. for each neg value I need to identify min(j+3) 3. end with this code: eq[i,j]<- ifelse(mat.r[i,j] < (0.5*mat.s[i,j]), mat.all[i,j], 0) This is the code I have so far. I have tried several different methods but I keep getting the same error message that the condition has length >1 and only

Hi I have a matrix (4 x 950) and I want to remove 3 rows, where the values from the first column are 713, 714 and 715. I can select the rows, one by one, with mat[mat$first==713,] mat[mat$first==714,] ... but I'm unable to (i) select the 3 rows at once, (ii) select the matrix excluding those rows. How can I do it ? Thanks EJ

Full_Name: Jerome Asselin Version: 1.3.0 OS: Windows 98 Submission from: (NULL) (24.77.112.193) I am having accuracy problems involving the computation of inverse of nonnegative definite matrices with solve(). I also have to compute the Choleski decomposition of matrices. My numerical problems involving solve() made me find a bug in the chol() function. Here is an example. #Please, load the

Dear List: I am having some difficulty constructing a matrix that must take a specific form. The matrix must be have a lower block of non-zero values and the rest must all be zero. For example, if I am building an n X n matrix, then the first n/2 rows need to be zero and the first n/2 columns must remain as zero with all other elements having a non-zero value that I specify. For example, assume

My goal is to store the DWT coefficients from a number of time series in such a way to be able to extract subsets satisfying giben conditions. I have defined the following 11 matrices whose x-axis represent time intervals and y-axis represent the number of time series: MS <- 11 d1.mat <- matrix (data=list(), nrow=TotNumCycles, ncol=2^(MS-1)) d2.mat <- matrix (data=list(),

I created a small example to show something that I do a lot of. "scale" data by month and return a data.frame with the output. "id" represents repeated observations over "time" and I want to scale the "slope" variable. The "out" variable shows the output I want. My for..loop does the job but is probably very slow versus other methods. ddply

There was a BioConductor thread today where the poster wanted to find pairwise difference between columns of a matrix. I suggested the slow solution below, hoping that someone might suggest a faster and/or more elegant solution, but no other response. I tried unsuccessfully with the apply() family. Searching the mailing list was not very fruitful either. The closest I got to was a cryptic chunk