similar to: fixed trimmed mean for group

Hello...i want to find the empirical rate for type 1 error using fixed trimmed mean. To make it easy, i'm referring to journal given by this website http://www.academicjournals.org/ajmcsr/PDF/pdf2011/Yusof%20et%20al.pdf. I already run the programme and there is no error in it but i got zero for the empirical rate of type 1 error. The empirical rate for the type 1 error given in the journal

Hello everyone, I want to calculate type I error rate for modified F statistic for one way robust anova. I need to find the j group trimmed mean and winsorized sum of squared deviations. Here I attached my code for j=2 to make it simple. Originally I have j=4. Hope you can help. I need to run it for 1000 times My problem is: i) the value of F-test obtain from my simulation below is in negative

Hello Everyone, My name is Thomas and I have been using R for one week. I recently found your site and have been able to search the archives of posts. This has given me some great information that has allowed me to craft an initial design to an inquiry I would like to make into the breakdown of McNemar's test. I have read an intro to R manual and the posting guides and hope I am not violating

Dear UseRs, MY PROBLEM IS A SMALL PIECE OF A REAL BIG AND A COMPLICATED PROBLEM. IF I DELIBERATE IN A VERY SIMPLE WAY THEN ALL I WANT IS TO PUT ALL THE POSSIBLE COMBINATIONS OF 75 DISTANCE MATRICES (BY TAKING 4 MATRICES, MORE COMMONLY 75C4), in the following equation. t<-as.matrix((MAT1)^2+(MAT2)^2+(MAT3)^2+(MAT4)^2+,upper=T,diag=T)) Then "1215450" values of "t"(one for

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 <-

> > 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

rm(list=ls()) yx.df<-read.csv("c:/MK-2-72.csv",sep=',',header=T,dec='.') dim(yx.df) #get X matrix y<-yx.df[,1] x<-yx.df[,2:643] #conver to matrix mat<-as.matrix(x) #get row number rownum<-nrow(mat) #remove the constant parameters mat1<-mat[,apply(mat,2,function(.col)!(all(.col[1]==.col[2:rownum])))] dim(yx.df) dim(mat1) #remove columns with numbers of

Hi, I had the following code: testp <- rcorr(t(datcm1),type = "pearson") mat1 <- testp[[1]][,] > 0.6 mat2 <- testp[[3]][,] < 0.05 mat3 <- mat1 + mat2 The resulting mat3 (smaller version) matrix looks like: NA 0 0 0 0 NA 0 NA 0 0 NA 2 0 0 2 NA To get to the number of times a '2' appears in the rows, I was

Sorry for the verbose example. I want to row bind two matrices, and all works except I want the column labelled "row" to be sequential in the new matrix, shown as "mat3" here, i.e. needs to be 1:6 and not 1:3 repeated twice. Any suggestions? Thanks J > colnm1 <- c("row","ti","counti") > colnm2 <-

Dear R heleprs   Suppose I have following data   Scenarios combination_names     series1    series2 Sc1 MAT2 GAU1 7.26554 8.409778 Sc2 MAT2 GAU2 7.438128 8.130275 Sc3 MAT3 GAU1 8.058422 8.06457 Sc4 MAT1 GAU2 8.179855 8.022071 Sc5 MAT3 GAU2 8.184033 8.191831 Sc6 MAT3 GAU2 7.50312 8.232425 Sc7 MAT1 GAU2 7.603291 8.200993 Sc8 MAT1 GAU1 8.221755 8.380097 Sc9 MAT3 GAU2 7.904908

Hi, How to turn a character string into an unevaluated R object? I want to load some files in a directory into data matrix R objects. I could do this with read.table and assign (see below). Then, I want to turn the character string representing a file name (the evaluated expression of i) into an unevaluated R object. Basically, I want to create matrices whose names are the same as the related file

Dear all, Ket say I have 3 matrices : mat1 <- matrix(rnorm(16), 4) mat2 <- matrix(rnorm(16), 4) mat3 <- matrix(rnorm(16), 4) Now I want to merge those three matrices to a single one with dimension 4*3=12 and 4 wherein on resulting matrix, row 1,4,7,10 will be row-1,2,3,4 of "mat1", row 2,5,8,11 will be row-1,2,3,4 of "mat2" and row 3,6,8,12 will be row-1,2,3,4 of

Dear all, I have a collection of 5000 entries which represent the evolutionary rates of 3 animals. I would like to show the differences between the rates of all 3 animals and have tried using the function parallel (from the lattice package) and pairs() function. The parallel function would have been perfect save for the large number of data (5000). The pairs() function doesn't show

Hi.. i have an expression of the form: model1<-nls(y~beta1*(x1+(k1*x2)+(k1*k1*x3)+(k2*x4)+(k2*k1*x5)+(k2*k2*x6)+(k3*x7)+(k3*k4*x8)+(k3*k2*x9)+(k3*k3*x10)+ (k4*x11)+(k4*k1*x12)+(k4*k2*x13)+(k4*k3*x14)+(k4*k4*x15)+(k5*x16)+(k5*k1*x17)+(k5*k2*x18)+(k5*k3*x19)+

Here is a drop-in replacement for the R incomplete beta function. src/math/pbeta.c It is a slightly modified version of the cephes library one from Netlib. In the few cases I tried it seems to give at least 14 digit agreement with the one in S-PLUS (its hard to get more). I'm not sure what performance is like. I'd like to know if it helps with some of the problems which have been

Hi, I have a question about how to obtain the union of several data frame rows. I'm trying to create a common key for several tests composed of different items. Here is a small scale version of the problem. These are keys for 4 different tests, not all mutually exclusive: id q1 q2 q3 q4 q5 q6 1 A C 2 B D 3 A D B 4 C D B D I would like

On my CentOS 5 box, in a C++ program that does much arithmetic, including numerous matrix multiplications, I have a situation in in which the result depends on the nature of nearby I/O. Thus, with all arithmetic done with type double, and where values are mostly in the range [-1.0e0,+1.0e0] or nearby, I do: cerr << "some stuff" << endl; mat3 = matmult(mat1,mat2); I

Dear R-gurus, Just supose I have a dara.frame that looks like myDF<-read.table(stdin(),head=T,sep=",") codID,namesp,k1,k2,k3,k4 1,spA,2,5,6,3 2,spB,4,5,4,6 3,spC,2,1,5,6 4,spC,5,4,3,2 5,spD,1,2,3,4 6,spE,2,4,3,1 I need to update the columns k1-k4 with the namesp, but considering the math between Kx and codID. My desired output must looks like: codID,namesp,k1,k2,k3,k4

Hi, I'm almost there with my Yasm printer, however, I've stumbled upon this. Using this: ; ModuleID = 'data.u' %window = type { %visobj, %vec2, %vec2, %vec2, %string, %color, i32, i32, %string, %string, %string, i1, i1, i1, i1, i1, i1, i32, i8* } %visobj = type { %object, i1, i1, i1, i1, %color, %vec4, %vec4, %vec4, %vec4, i32, %mat4, %mat4, %mat4, %mat4, %material*,

Hi all, I'd like to compare all levels of my interaction with each other. I read the pdf 'Additional multcomp Examples' but even though there is an example with an interaction it doesn't work for me when I want to compare within and between groups. Here is an example: #### d.fr<-data.frame(id=rep(1:16,3),treat1=rep(as.factor(LETTERS[1:3]),each=