similar to: how to remove "numeric(0)" component from a list

Hi all, I was wondering whether it is possible to use the lapply() function to alter the value of the input, something in the spirit of : a1<-runif(100) a2<-function(i){ a1[i]<-a1[i-1]*a1[i];a1[i] } a3<-lapply(2:100,a2) Something akin to a for() loop, but using the lapply() infrastructure. I haven't been able to get rapply() to do this. The reason is that the "real"

Hi there, I run two regressions: y = a1 + b1 * x + e1 y = a2 + b2 * z + e2 I want to test against the null hypothesis: b1 = b2. How do I design the test? I think I can add two equations together and divide both sides by 2: y = 0.5*(a1+a2) + 0.5*b1 * x + 0.5*b2 * z + e3, where e3 = 0.5*(e1 + e2). or just y = a3 + 0.5*b1 * x + 0.5*b2 * z + e3 If I run this new regression, I can test against

I have a problem with expressions. I am trying to create a title where the parameter of interest is displayed as a Greek character. Which parameter is being considered is stored in a character variable. As an example, if I have param <- "alpha" and then do plot(0, 0, main = bquote(Parameter==.(param))) then in the title I get "Parameter = alpha", whereas I want the

I have a matrix of frequency counts from 0-160. x<-as.matrix(c(0,1,0,0,1,0,0,0,1,0,0,0,0,1)) I would like to apply a function creating a new column (x[,2])containing values equal to: a) log(x[m,1]) if x[m,1] > 0; and b) for all x[m,1]= 0, log(next x[m,1] > 0 / count of preceding zero values +1) for example, x[1,2] should equal log(x[2,1]/2) = log(1/2) = -0.6931472 whereas x[3,2] should

Hi, How can I check if a certain ... argument has been passed on to my user-defined function or not? foo <- function(data, ...) { ### here I want to check whether xlab was passed with the ... arguments ### or if the ... arguments did not contain an xlab argument } I tried missing(xlab) , exists(xlab) and several other things but did not find a solution. TIA, Mark

Hi, When qqnorm on a vector of length 10M+ I get a huge pdf file which cannot be loaded by acroread or evince. Any suggestions? (apart from sampling the data). Thanks. -- Sam Steingold (http://sds.podval.org/) on Ubuntu 11.10 (oneiric) X 11.0.11004000 http://mideasttruth.com http://honestreporting.com http://camera.org http://openvotingconsortium.org http://pmw.org.il

Hi, I have a question regarding the image function. Is there a way to specify a separate color set for each column in the matrix? TIA, ajar. [[alternative HTML version deleted]]

Hi, I am having difficulty entering a 'programmable' argument into the multinom function from the nnet package. Interactively, I can get the function to work fine by calling it this way: z1=multinom(formula = class.ind(grp[-outgroup])~ (PC1 + PC2 + PC3), data=data.frame(scores)) However I need to be able to change the number of variables I am looking for in 'scores' and so am

I was playing around a bit to see how I could find the two points in a set of points (or ordered pairs) furthest from each other. Here's what I did: 1) created a Nrow by 2col matrix, so each row contains an x,y coordinate pair. 2) fed the matrix to a nested mapply (cv is my matrix): mapply(function(k,l) mapply(function(x,y,a,b) +

Dear list; I just created a utility function that replicates what I have done in the past with Excel or OO.org by putting a formula of the form =sum($A1:A$1) in an upper-corner of a section and then doing a "fill" procedure by dragging the lower-rt corner down and to the right. When divided by the grand sum of the entries this function then calculates a 2D-discrete-ECDF. I

Hello R users, I have gene expression data of two groups of genes (large and small). Gene expression intensities of those genes are classified into 1 to 10 levels. What I want is to make a random set of genes that have the same levels as the small group from large group using sample(). I used smallvec to hold the number of genes in each levels (1 to 10) for small group, largevec for large group.

Hello I'm trying to run a fortran code which use LAPACK subroutines. I think I should use some points shown in the manual 5.5 Creating shared objects but it is too technical for me :-(... Could anyone help me for the procedure to do: -which part of the manual is relevant for this type of question? actually I'm speaking from writing R extensions, should I read R admin? -point 1.2

I am doing cluster analysis [hclust(Dist, method="average")] on data that potentially contains redundant objects. As expected, the inclusion of redundant objects affects the clustering result, i.e., the data a1, = a2, = a3, b, c, d, e1, = e2 is likely to cluster differently from the same data without the redundancy, i.e., a1, b, c, d, e1. This is apparent when the outcome is visualized

Dear fellow R users, I am now investing time in learning how to use compiled C code to produces functions that can be used in R. I am just starting, and there is much that I need to learn, so I have a question that might be straight forward. I am learning how to use function in the C library GSL (gnu scientific library), to write C code, that I then plant to use in R. Is there any problem in

Hi all, I have some rough code to sample consecutive integers with length according to a vector of lengths #sample space (representing positions) pos<-c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20) #sample lengths lengths<-c(2,3,2) From these two vectors I need a vector of sampled positions. the sampling is without replacement, making things tough as the sampled integers need

parseNamespaceFile() doesn't seem to detect misspelled directives. Looking at its code I see switch(as.character(e[[1L]]), <lots of args omitted here>, stop(gettextf("unknown namespace directive: %s", deparse(e)), call. = FALSE, domain = NA)) but this doesn't seem to function as I expect, viz. to stop with an error if I type a wrong directive.

I'm ordering "The R Book" and hope to learn a lot more about R. In a meantime, I have a matrix of digits and I would like to look for a column that contains zeroes and remove the entire column from the matrix. I can write a piece of R code to do that (and it works); however, I think the R-experts have more tricks to do such a 'simple' thing. Many thanks in advance.

All: I am trying to fit a mixture of 2 normals with > 110 million observations. I am running R 2.5.1 on a box with 1gb RAM running 32-bit windows and I continue to run out of memory. Does anyone have any suggestions. Thanks so much, Tim [[alternative HTML version deleted]]

Dear R-helpers, I am very new to R and trying to run the conditional logit model using "clogit " command. I have more than 4000 observations in my dataset and try to predict the dependent variable from 14 independent variables. My command is as follows clmtest1 <- clogit(Pin~Income+Bus+Pop+Urbpro+Health+Student+Grad+NE+NW+NCC+SCC+CH+SE+MRD+strata(IDD),data=clmdata) However, it

Dear R users, As substitute() help page points out: Substituting and quoting often causes confusion when the argument is 'expression(...)'. The result is a call to the 'expression' constructor function and needs to be evaluated with 'eval' to give the actual expression object. And indeed I am confused. Consider: > dat <- data.frame(x=1:10,