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Hi! I'm trying to implement in R in an easy way the negative reflection method described in Silverman (1986) on p.31, ie I have a non-negative dataset and would like to estimate the density by applying a reflection method where the reflected points have weight -1. I thought there should be a way to evaluate the wanted kernel at the required points, in other words to calculate formula (2.16):

Hi I am sure there is a function out there already but I couldn't find it. I have SNP data, that is, a matrix which contains in each row two characters (they are different in each row) and I would like to convert this matrix to a binary one according to the minor allele frequency. For non-geneticists: I want to have a binary matrix for which in each row the 0 stands for the less frequent

Hi R-Help! I am trying to use R2WinBUGS but I get the following error message in WinBUGS (and there must be something wrong with my R statement as I tried it directly in WinBUGS and it worked): display(log) check(C:/Documents and Settings/Daikon/Roche/pop_model.txt) model is syntactically correct data(C:/Documents and Settings/Daikon/Roche/data.txt) expected key word structure compile(7) ...(and

Hi I have sent a previous email "Error in dyn.load()" for which, shame on me, I later found a partial answer. I have been trying to look into what I exactly need to include into Makevars and where it needs to be located and have not found a satisfying answer yet. Maybe the following questions are helpful for other people as well. Again, I am trying to include a C function tools.c into

Hi I was wondering if there was a way to run system when there is e.g. a C program which is not totally command-line driven. That is, I have a C program which requires manual input of options into the shell during the run. I would like to run this program from R and as far as I have seen system() does not handle manual options (?). Is there thus a way to use these C programs anyway through R

Dear R Users, I'm looking for a package that allows to test hypothesis about a homogeneity of odds ratio in k 2x2 tables. I know that Breslow-Day is suitable but does anybody could me point out a package? I found diffR, but as far as I see this package is for IRT theory. Best, Robert

Using Trellis, am successfully setting up a number of panels (25) in which I have two box and violin plots. I would like to colour - one plot as RED and the other as BLUE (in each panel). I can do that with the box plots, but the violin density areas just take on one colour. My basic call is as follows: bwplot(rmsd ~ file | code, data=spread_data.filtered, panel = function(...,

 Hi, Is there any function available to do stepwise selection of variables in Conditional(matched) logistic regression( clogit)? step, stepwise  etc are failing in case of conditional logistic regression. Please help.  Thanks P.T. Subha [[alternative HTML version deleted]]

HI, I am using lmer() for a simple mixed effects model. The model is of the form logit(y)~ x + (1|z), where x is an indicator variable and z a multi-level factor. I would like an estimate of the response variable (either y or logit y) with an associated confidence interval for a given value of x. There does not appear to be a predict function written for lmer(). The output for the fixed

Hi I would like to produce a red shading I figured the easiest way to do that would be to use rgb in the following way: a <- seq(0,0.9,by=0.1) redshade <- rgb(red=1,green=a, blue=a) However, I don't really know how to plot things using hexadecimal colors. I used a function which tries to find the closest color to the rgb shades but it didn't work very well. Any

Hi R-Help! My question: I have lifetime/failure data of machines with different stress levels and i think an weibull/extreme value distribution would fit this data. So I did: model1 <- survreg(Surv(lfailure)~stress,data=steel,dist="extreme") (where lfailure=log(failure)) Now I would like to do a likelihood ratio test to test the hypothesis H0: location parameters of the

Hi R-Users! I fitted a negative binomial distribution to my count data using the function glm.nb() and obtained the calculated parameters theta (dispersion) and mu. I would like to simulate values from this negative binomial distribution. Looking at the function rnbinom() I was looking at the relationship between the two possible parametrizations of the negative binomial and found that for this

Hi There must have someone already posted this question but I still have not figured how I could do this: Say I have var.1 var.2 var.3 which are large matrices. I would like to do the following loop: for(i in 1:3){ # Pick var.i and do something with it } How can I tell R to do this? Thanks for any comments. Hadassa [[alternative HTML version deleted]]

Hi, I was wondering if there is a way to control the strip size in xyplot for example using the strip.default function. Or do I need to redraw the strips by myself? I would like to make the strip slimmer and I have reduced the font size using cex. However, I don't know how to change the size of the strip. Thanks for any tips. Hadassa [[alternative HTML version deleted]]

Hi R-users! I am trying to create a what I call inflated array (maybe there is already some other name for that). It is an array that changes dinamically its dimensions, e.g. the higher the number of third dimensions, the more rows in the array. So for example the array could look like the following: , ,1 1 2 3 4 , , 2 5 6 7 8 9 10 11 12 , , 3 13 14 15 16 17 18 19 20 21 22 23 24 Has

Dear R users! I used lme to fit a mixed model with random intercept and spatial Gaussian correlation i.e. I fitted a model of the following form: Y = X*beta + error and error = U + W(t) + Z where U is the random intercept (normally distributed), W(t) the stationary Gaussian process and Z also a normally distributed (the residual) rv. Each of these three random variables have a variance which

Hi everyone! This must be a common question but I have not found an answer to it in the archives yet. I am producing four plots with par(mfrow=c(2,2)). The x-axis is the same for all of them but the y-axis is different. What I would like to do is to have a different range of the y-axis and different intervals between tick marks. BUT I would like to have the same number of tick marks and I would

hi,R users, Now I have some scatter figures, is there some method can plot equalprobable error ellipse ? -- TANG Jie Email: totangjie@gmail.com Tel: 0086-2154896104 Shanghai Typhoon Institute,China [[alternative HTML version deleted]]

Hi R users! I have a likelihood ratio statistic that depends on a parameter delta and I am trying to get confidence intervals for this delta using the fact that the likelihood ratio statistic is approx. chi-squared distributed. For this I need to maximize the two likelihoods (for the ratio statistic) one of which depends on delta too and I am trying to use the function "mle". But

With the approach of R 2.12.0: with mild apologies for re-opening this perennial issue: is there any hope, if appropriate patches are submitted, of adding a drop.levels argument (with default equal to FALSE to preserve backward compatibility/efficiency) to the subset function ... ? If not, would a patch to the documentation and/or the R FAQ be accepted? This does seem to be a continuing