similar to: hi, how can we avoid maskiing error in R

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 All, I'm still pretty new to using R - and I was hoping I might be able to get some advice as to how to use 'apply' or a similar function instead of using nested for loops. Right now I have a script which uses nested for loops similar to this: i <- 1 for(a in Alpha) { for (b in Beta) { for (c in Gamma) { for (d in Delta) { for (e in Epsilon) { Output[i] <-

Dear expeRts, recently I asked for a nice way to re-program a problem without using control constructs such as "for" or "sapply(1:length(x), ...". Is there a way to program a random walk with a reflecting boundary without resorting to such constructs? A working solution is ranwalk <- function(length, bound) { k <- cumsum(sample(c(-1, 1), length, replace=TRUE))

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]]

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) +

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

Dear R user, I'm trying to find a solution for optimizing my code. I have to run a 50.000 iteration long simulation and it is absolutely necessary to have an optimized code. I have to do this operation *sum_t ( t(X_t) %*% A %*% X_t )* where X_t is a (d*k) matrix which changes in time and A is a constant in time (d*d) matrix. I have put all my X_t in a three dimensional array X of dimension

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.

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

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

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

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 R folks, I have a massive array (object name "points") in the following form [,1] [,2] [1,] 1369 22 [2,] 1370 22 [3,] 1368 23 [4,] 1369 23 [5,] 1370 23 [6,] 1371 23 (10080 rows truncated) These represent pixel coordinates of interest in a jpeg image. I need to find the distance from each point to all other points of interest. The only way I can see to do this

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.