similar to: find confounder in covariates

Hi I'm trying to set up a simulation problem without resorting to (m)any loops. I want to set entries in a data frame of zeros ('starts' in the code below) to 1 at certain points and the points have been randomly generated and stored in a separate data.frame ('sl'), which has the same number of columns. An example of the procedure is as follows: ml <-

I spent a lot of time searching and came up empty handed on the following query. Is there an equivalent to rowSums that does product or cumulative product and avoids use of apply or looping? I found a rowProd in a package but it was a convenience function for apply. As part of a likelihood calculation called from optim, I?m computing products and cumulative products of rows of matrices with

I have a situation where I'm filling out a dataframe from a database. Sometimes the database query doesn't get anything, so I end up trying to place NULL in the dataframe like below. > temp <- NULL > xmat <- as.data.frame(matrix(NA, 2, 3)) > xmat[1, 2:3] <- temp Error in if (m < n * p && (n * p)%%m) stop(gettextf("replacement has %d items, need %d",

A short function I wrote for the purpose of evaluating scales made up of a number of questionnaire items. It provides Cronbach's Alpha, both unstandardized and based on standardized items. It also provides item statistics which include item-total correlations (corrected) and item-removed alpha. Thought some of you might find it useful. I would also appreciate any programming tips or

Hi, I have a matrix and time series "xmat". I have no problem executing any matrix functions except t(xmat) which gives the following error message. My question if "xmat" is a matrix why I can not execute this matrix function?? converting the time series and matrix into a data frame solves the problem >dim(xmat) [1] 98 7 > t(xmat) Error in "tsp<-"(*tmp*,

dear all. Would someone be kind and willing to explain the code below for a person who has never used R? ( that is if one has enough time and inclination) It implements gillepsie's stochastic algorithm for Lotka Volterra model. What would help me tremendously is to see the breakdown of the line by line code into plain english. thanks for any insights or other comments. sean

I'm working on the next version of coxme, one step of which is converting the bdsmatrix library from Splus to R. Actually, it is a conversion from S4 methods as first described in the Green book to S4 methods as they currently exist. Mostly it's going ok, but not entirely. 1. The biggest issue is lack of documentation. The online help pages have not been a help; they keep saying

Hi, I use sapply very frequently, but I have recently noticed a behavior of sapply which I don't understand and have never seen before. Basically, sapply returns what looks like a matrix, says it a matrix, and appears to let me do matrix things (like transpose). But it is also a list and behaves like a list when I subset it, not a vector (so I can't sort a row for instance). I

Dear R-Help I am running apply on a data.frame containing factors and numeric columns. It appears to convert are columns into as.character? Does it convert data.frame into matrix? Is this expected? I wish it to recognise numerical columns and round numbers. Can I use another function instead of apply, or should I use a for loop in the case? > summary(xmat) A B

I get different results from match.call(), according to whether a function is dispatched via S3 or S4. Specifically, when I use S4 dispatch in the following example, the match.call() result is of length 1 less than I expect. I need to add an extra comma to get the same results as in the S3 method. --------example setClass("foo",representation("matrix"))

As of rev. 61035 in r-devel, setRefClass() now returns a generator function, as setClass() has done since 2.15.0. The convenient style is now: mEdit <- setRefClass("mEdit",......) xx <- mEdit(data = xMat) instead of xx <- mEdit$new(data = xMat) The returned object still has fields and methods accessible as before. See the "Value" and "Reference Class

R-users E-mail: r-help@r-project.org Hi! R-users. http://finzi.psych.upenn.edu/R/library/mvpart/html/xpred.rpart.html says: data(car.test.frame) fit <- rpart(Mileage ~ Weight, car.test.frame) xmat <- xpred.rpart(fit) xerr <- (xmat - car.test.frame$Mileage)^2 apply(xerr, 2, sum) # cross-validated error estimate # approx same result as rel. error from printcp(fit) apply(xerr, 2,

Hello, I am using e1071 to run support vector machine. I would like to plot the data with lattice and specifically show the hyperplanes created by the system. I can store the hyperplane as a contour in an object, and I can plot one object at a time. Since there will be thousands of elements to plot, I can't manually add them one by one to the plot, so I tried to loop into them, but only the

Hi all, Thanks to all who offered advice on using F95 in R. Now I'm trying to compile a test package using gfortran, Linux 2.4.21 and R 2.1.0. I was able to successfully compile and use a test F95 routine by setting my environment variables as follows in bash: export PATH=~/bin/:$PATH export F77=gfortran export LD_LIBRARY_PATH=~/bin/irun/lib export GFORTRAN_STDIN_UNIT=-1 Now I'm

Dear all, I'm new on R and this mailing list. We work on spatial rainfall estimation with R and Grass. We have a problem with the krige function from the sgeostat package. We would like to limit the estimated area with a polygon limit. I use a 50 points polygon to describe my work area. The krige function work quiet well without limit. But if I use this option I have the following error

Hi, I'm having a problem using sample() within a function. Basically I get an error reading: Error in sample(v, 1, prob = h) : non-positive probability Can anyone advise me as to the possible origin of this error? Here is my code #Discretised Gillespie algorithm function (From SMfSB, D.J. Wilkinson) gillespied=function (N, T=100, dt=1, ...) { tt=0 n=T%/%dt x=N$M

On Tue, Oct 27, 2020 at 6:04 PM Luigi Marongiu <marongiu.luigi at gmail.com> wrote: > > Hello, > I am using e1071 to run support vector machine. I would like to plot > the data with lattice and specifically show the hyperplanes created by > the system. > I can store the hyperplane as a contour in an object, and I can plot > one object at a time. Since there will be

Hi all, I have a x, y matrix of numbers (usually ranging from 0 to 40). I need to group these numbers and assign a color to each group (for example 0 to 15 - Blue, 16-30- Yellow, and 31-40- Red). Then I need to draw a rectangular matrix which contains X x Y boxes and each box has the corresponding value from the input matrix and is also colored according to which group (i.e red, yellow,

Hello R users,  I am trying to obtain a direct adjusted survival curve. I am sending my whole code (see below). It's basically the larynx cancer data with Stage 1-4. I am using the cox model using coxph option, see the fit3 coxph. When I use the avg.surv option on fit3, I get the following error: "fits<-avg.surv(fit3, var.name="stage.fac", var.values=c(1,2,3,4), data=larynx)

Dear useRs, i want to split a matrix having 1116rows and 12 columns. i want to split that matrix into 36 small matrices each having 12 columns and 31 rows. The big matrix should be splitted row wise. which means that the first small matrix should copy values which are in first 31 rows and 12 columns of the big matrix. similarly 2nd small matrix should contain values from 32nd to 63rd row of the