search for: famprevm

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"

...-15) Platform: i386-apple-darwin9.8.0/i386 (32-bit) locale: [1] C attached base packages: [1] stats graphics grDevices utils datasets methods base > Charles C. Berry Dept of Family/Preventive Medicine cberry at tajo.ucsd.edu UC San Diego http://famprevmed.ucsd.edu/faculty/cberry/ La Jolla, San Diego 92093-0901

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 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

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, 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 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

...producible code. >>>> >>> Charles C. Berry (858) 534-2098 >>> Dept of >> Family/Preventive Medicine >>> E mailto:cberry at tajo.ucsd.edu UC San Diego >>> http://famprevmed.ucsd.edu/faculty/cberry/ La Jolla, San Diego >>> 92093-0901 >>> >>> ______________________________________________ >>> R-help at r-project.org mailing list >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide...

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 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 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 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

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 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

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

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 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,