similar to: avoiding loops?

Dear Mr. Therneau, Mr. Fox, or to whoever, who has some time... I don't find a solution to use the "survfit" function (package: survival) for a defined pattern of covariates with a Cox-Model including a time dependent interaction term. Somehow the definition of my "newdata" argument seems to be erroneous. I already googled the problem, found many persons having the

Hi, anybody know why this not works for several plots ? When i set onefile=T the plots are stacked one about another , onefile=F only the first plot is shown in AllbusMeansPlots.svg. [h2 is a data.frame] ......hist and sapply works for several plots nice with RSvgDevice ! Maybe setting the title after apply is a problem, but until yet i didn't found a better solution ? library(RSvgDevice)

Hi: First my apologies for cross-posting. A few days back I posted my queries ar R-sig-geo but did not get any response. Hence this post. I am working on two parcel-level housing dataset to estimate the impact of various variables on home sale prices. I created the spatial weight metrics in ArcGIS 10 using sale year of four nearest houses to assign weights.  Next, I ran LM tests and then ran

When I installed R 2.0.1 (replacing 1.9.0) for Windows, a code using "model.response" began acting up. Here are the first several lines of a code I had been tweaking for a spatial model (the code is mostly that of Roger Bivand--I am adapting it to a slightly different data structure and the problem I'm sure is with my changes, not his code). <command name> <- function

Dear R-users, I've been working with three different data sets (X, Y and Z) with the same dimension (i.e, n \times k). What I needed to do was to conform a 4th data set, i.e. FINAL, which first row was the X's first row, its second row was the Y's first row, and its third row was the Z's first row, and so on. My code is below. Is it possible to avoid the loop? Thanks in advance,

Dear R users, I'd like to build a simple design matrix in a efficient way. I naively wrote the code below. #### n = 15 k = 3 nbPerGrp = c(5,5,5) xT <- list() for (i in 1:k){ xT[[i]] <- rep(0, k) xT[[i]][i] <- 1 } X <- matrix(nrow = n, ncol = k) #design matrix for (i in 1:nbPerGrp[1]){ X[i,] <- xT[[1]] } for (i in 1:k-1){ for (j

thank you, achim. I will try chol2inv. sandwich is a very nice package, but let me make some short suggestions. I am not a good econometrician, so I do not know what prewhitening is, and the vignette did not explain it. "?coeftest" did not work after I loaded the library. automatic bandwidth selection can be a good thing, but is not always. as to my own little function, I like the

http://biomet.oxfordjournals.org/cgi/reprint/86/3/677 biometrika1999 http://biomet.oxfordjournals.org/cgi/reprint/94/4/1006 biometrika2000 Hi All: I just want to try some luck. I am currenly working on my project,one part of my project is to reanalysis the kenward cattle data by using the method in Mohsen's paper,but I found I really can get the same or close output as he did,so,any

Hello my friends, here is a code I wrote with no loops on matrix that is taking too long (2 seconds and I call him 720 times --> 12 minutes): mat1 and mat2 are both matrix with 103 columns and 164 rows. sequence <- matrix(seq(1 : ncol(mat1))) returns <- apply(sequence, 1, function, mat1= mat1, mat2 = mat2, day = 1) function<- function(mat1, mat2, colNb, day){

Hi everyone. I'm using matrix product such as : #Generate some data NCols = 5 NRows = 5 A = matrix(runif(NCols*NRows), ncol=NCols) B = matrix(runif(NCols*NRows), ncol=NCols) #First calculation R = A%*%B for(i in 1:100) { R = R%*%B } I would like to know if it was possible to avoid the loop by using something like mapply or anything else. Tx in advance, Phil -- View this message

Hi all, I have this information on a file ht.txt, imagine it is a data frame without labels: 1 1 1 8 1 1 6 4 1 3 1 3 3 And on other table called "pru.txt" I have sequences similar this 4 1 1 8 1 1 6 4 1 3 1 3 3 1 6 1 8 1 1 6 4 1 3 1 3 3 1 1 1 8 1 1 6 4 1 3 1 3 3 6 6 6 8 1 1 6 4 1 3 1 3 3 I want to now how many positions are identical between each row in pru compared with ht. n and m

Hi, have anybody a hint how i could avoid the cumbersome way (..especially the value part) change the data representation from n column data.frame to an stacked representation. many thanks Christian #example data dfw <- as.data.frame(matrix(runif(10*10),ncol=10)) dfw$group <- sample(c("X","Z"),nrow(dfw),replace=T,prob=c(0.75,0.25)) # change var <-

Hi, I need some help improving this ugly code I wrote. I would like to shift forward a zoo object, matrix, ts, or list by "shift" items (default 1) and fill the holes with 0's. The code below works, but it looks ugly. I could write a function lag.zerofill() which calls the two functions below depending on the class() of the item passed in, but that feels very unlike R. What is

Hi, sapply((1:NCOL(hermes)),function(x) hist(hermes[,x],main=names(hermes)[x])) .......this works , but i would like use it with apply to generate many plots in one step! #################################################################### >>apply((1:ncol(hermes)),2,function(x) hist(hermes[,x],main=names(hermes)[x])) Error in apply(1:ncol(hermes), 2, function(x) hist(hermes[, x], main =

Hello! I have a data set: set.seed(123) y<-data.frame(week=seq(as.Date("2010-01-03"), as.Date("2011-01-31"),by="week")) y$var1<-c(1,2,3,round(rnorm(54),1)) y$var2<-c(10,20,30,round(rnorm(54),1)) # All I need is to create lagged variables for var1 and var2. I looked around a bit and found several ways of doing it. They all seem quite complicated - while in

Hi I hope this is going to the right place. I am trying to write a program which uses KernSmooth library to estimate mutual information between two time series at various different lags. At the moment it’s producing negative values, which is supposed to be impossible (something is fishy). I am summing across one row of the matrix to get p(value is in bin x) and summing across the columns to get

Hi, i get only one value, but expect ncol values - what's wrong ? test <- function(){ for (i in 1:ncol(configData)) x <- subset(configData, Q71 == 1 & configData[,i] ==1 , select = configData[,i]) y <- (dim(x)[1]/dim(configData)[1])*100 return(y) } thanks for advance & regards, Christian

How do you specify matrix location a[i,j] (or a[i-1,j], etc.) in a "for" loop? I am looking for a flexible method of indexing neighbors over a series of lags (1,2,3...) and I may wish to extend this method to 3D arrays. Example: Data matrix > fun [,1] [,2] [,3] [1,] 1 5 9 [2,] 2 6 10 [3,] 3 7 11 [4,] 4 8 12 For each element a[i,j] in

HI, You may try this: dat1<- read.table(text=" CustID TripDate Store Bread Butter Milk Eggs 1 2-Jan-12 a 2 0 2 1 1 6-Jan-12 c 0 3 3 0 1 9-Jan-12 a 3 3 0 0 1 31-Mar-13 a 3 0 0 0 2 31-Aug-12 a 0 3 3 0 2 24-Sep-12 a 3 3 0 0 2 25-Sep-12 b 3 0 0 0 ",sep="",header=TRUE,stringsAsFactors=FALSE) dat2<- dat1[,-c(1:3)] res<- lapply(seq_len(ncol(dat2)),function(i)

Hi, Would a specialist of the "point" or "plot" functions try the following: mat<-matrix(c(1.836767,4.025989,0.6396777,0.3764444),ncol=2) plot(mat) points(mat[1,],col="red") ..A lag appears on x for mat [1,1] between the two displays. I wonder if this example may be due to a bug or to the mis-use of a matrix in the plot() points() functions. In case of