similar to: List of multidimensional arrays

Dear R users, I have a 51 by 51 matrix of p-values (named as pvalue_MA). I want to present graphically this matrix in a plot (filled contour plot) where both axes represent probabilities. I have also added a grid in this plot. I want to highlight in white the cells of the grid that represent p-values smaller than the (common) significance threshold, 0.05. The code from this plot is colored in

Dear all, I want to obtain the following result [[1]] , , 1, 1 [,1] [,2] [1,] 1 1 [2,] 1 1 , , 2, 1 [,1] [,2] [1,] 1 1 [2,] 1 1 ................ , , 9, 1 [,1] [,2] [1,] 1 1 [2,] 1 1 , , 10, 1 [,1] [,2] [1,] 1 1 [2,] 1 1 [[2]] , , 1, 1 [,1] [,2] [1,] 1 1 [2,] 1 1 , , 2, 1 [,1] [,2] [1,] 1

I want to make a multi-dimensional array. To be specific I want to make the following array results<-array(0,dim=c(2,2,64,7)) This is the code I have created but it gives no result due to the error "subscript out of bound". x<-rep(7,7) # Missingness in intervention y<-rep(7,7) # Missingness in control

Dear all, I am trying to construct 25x31 different matrices of 2x2 dimension. Here is the problem: we have the following matrix matrix(c(54+s0, 43+s1, 56-s0, 67-s1), nrow=2, ncol=2, byrow=T) the values for s0 and s1 are c(0:24) and c(0:31), respectively. I wrote the following code without the desired results

Dear all, as you can see from the code I want to create *a panel of 11 contour plots through a iteration process*. I found a thread that address the issue of plotting many contour.plots in the same device, but it does not address my problem! I emphasize that the 11 contour plots must be appeared in the same device through an iteration process and NOT individually! par(mfrow=c(4,3)) # I want them

Dear R-list members, I need an help with the Multidimensional Scaling analysis (MDS). So far I used the cmdscale() command in R, but I did not get the perceptual map I would love to see, and I would like to know if it is possible to get it using R, and if yes how. I also had a look to the functions isoMDS() and sammoc() but with no luck. I summarize the experiment I performed, and I would ask you

I came across a post by Karl Knoblick regarding the modeling of longitudinal data (see https://stat.ethz.ch/pipermail/r-help/2007-May/132137.html). I am often asked by physicians to perform what Karl refers to in his post as option 1: to perform paired t-tests against baseline at each follow up time point (30 days, 90 days, 6 months, etc.). Unlike Karl's example, however, many of the trials

Dear R-users, In a randomized placebo-controlled within-subject design, subjects recieved a psycho-active drug and placebo. Subjects filled out a questionnaire containing 15 scales on four different time points after drug administration. In order to detect drug effects on each time point, I compared scale values between placebo and drug for all time conditions and scales, which sums up to

Dear All, I met problems when doing contrast and now really need some help in the model below: Fit=gam(y~treat+SEQUENCE+PERIOD+SEX+s(x),data=dat, random=list(SUBJID=~1),correlation=corAR1(form=~1|SUBJID)) And error message keeps coming out when I want to compare the differences between treatments: Diff=contrast(Fit, list(treat=treatment[-placebo.pos]),list(treat="Placebo"),

Hello. I have a 4 dimensional array and I want to fill in the slots with values which are a function of the inputs. Through searching the forums here I found that the function "outer" is helpful for 2x2 matrices but cannot be applied to general multidimensional arrays. Is there anything which can achieve, more efficiently than the following code, the job I want? K <-

Hello, I am planning a study with the main point to evaluate the interaction of two treatments, but for ethical reasons one cell is empty, that with patients receaving no treatment at all Treatment B

Hi, I am experimenting with using glht() from multcomp package together with coxph(), and glad to find that glht() can work on coph object, for example: > (fit<-coxph(Surv(stop, status>0)~treatment,bladder1)) coxph(formula = Surv(stop, status > 0) ~ treatment, data = bladder1) coef exp(coef) se(coef) z p treatmentpyridoxine -0.063 0.939 0.161

In the process of moving a number of my scripts from MATLAB -> R, I've discovered that there is no 'pure' equivalent of MATLAB's cell arrays, which I use quite often. Basically, I create matrices (as a cell array) where each element of the matrix is itself a matrix (e.g., 2x2 cell array where each element of the array is another matrix). I pass these cell arrays to various

I cannot seem to get a L'abbe plot to work on R. I do not understand what the X coordinates, or alternatively an object of class metabin, is supposed to mean. What is a class of metabin? Institute of Behavioral Genetics University of Colorado, Boulder Whitney.Melroy at Colorado.EDU

A student of mine wants to use R to do some nonmetric multidimensional scaling. According to the R FAQ, there's a package called pcurve that computes multidimensional scaling solutions, but I was not able to locate it the contrib page (I am a Windows user with R version 1.4.1). Can anyone tell me whether it is possible to do nonmetric multidimensional scaling with R, and if so, how? John

I managed with success to export a data frame of 367 columns and 37 rows to a txt file, but unfortunately I couldn't manage the same with the transposed data frame. Specifically, it seems like the notebook cannot "read" correctly 367 columns, so it reads the first 145 columns and it folds down the rest of them and consequently it folds down the respective data.

Hello, I think I am beginning to understand what is involved in the so-called "Type-I, II, ..." ANOVAS (thanks to all the replies I got for yesterday's post). I have a question that will help me (and others?) understand it better (or remove a misunderstanding): I know that ANOVA is really a special case of regression where the predictor variable is categorical. I know that there

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

Dear r-helpers, I have a question about multiple testing. Here an example that puzzles me: All matrixes and contrast vectors are presented in treatment contrasts. 1. example: library(multcomp) n<-60; sigma<-20 # n = sample size per group # sigma standard deviation of the residuals cov1 <- matrix(c(3/4,-1/2,-1/2,-1/2,1,0,-1/2,0,1), nrow = 3, ncol=3, byrow=TRUE, dimnames =

I am moving this to r-devel. The problem and solution below posted on r-help could have been a bit slicker if %*% worked with multidimensional arrays multiplying them so that if the first arg is a multidimensional array it is mulitplied along the last dimension (and first dimension for the second arg). Then one could have written: Tbar <- tarray %*% t(wt) / rep(wti, each = 9) which is a bit