similar to: Bayesian estimate of prevalence with an imperfect test

Dear list members, How can I replace the nested for loops at then end of the script below with more efficient code? # Begin script__________________________________________________ # Dichotomous scores for 100 respondents on 3 items with # probabilities of a correct response = .6, .4, and .7, # respectively x1 <- rbinom(100,1,.6) x2 <- rbinom(100,1,.4) x3 <- rbinom(100,1,.7) #

I was trying to plot some data in R. I used the following code to draw a loess fit and got the output as >?lines(lowess(log(abs(t(res))), log(abs(t(synthesised)))), col="red") Error in lowess(log(abs(t(res))), log(abs(t(synthesised)))) :?? NA/NaN/Inf in foreign function call (arg 1) Then I thought to use your Limma package for background correction. Do you think it's a right

Hi, I am doing kernel density plots, and am trying to make the lines thicker. I comparing three groups, in sm.density.compare. I tried changing lwd to make the line sthicker right on the density compare call, but was not able to do it. There is not an option in sm.options to specify line thickness, as well as cex.ylab or cex.xlab- I tried it and it does not change the thickness of the lines.

I am working with a model that I have to estimate a nonparametric function. The model is partial linear i.e. Y=X$\beta$ + f(z) + $\epsilon$ I am using the ' double residual methods' Robinson (1988) Speckman (1988) where I estimate a nonparametric function for each of the parametric variables in terms of the nonparametric one i.e. X[,i]=g(Z)+ u this is done because I need the $E(

Hello r-help, I'm fitting a model with lm() and using the orthogonal polynomials from poly() as my basis: dat <- read.csv("ConsolidatedData.csv", header=TRUE) attach(dat) nrows <- 1925 Rad <- poly(Radius, 2) ntheta <- 14 Theta <- poly(T.Angle..deg., ntheta) nbeta <- 4 Beta <- poly(B.Beta..deg., nbeta) model.1 <- lm( Measurement ~ Block + Rad + Theta + Beta

Dear all, Does anybody know how to get more evaluation points in performing Nonparametric analysis of repeated measurements data with "sm" library. The following command gives the estimation for 50 points, by I would like to increase to 100 points But I do not know how to do that. library(sm) provide.data(citrate, options=list(describe=FALSE)) provide.data(dogs,

Dear R users, I'm trying to fit a gamma-frailty model on a simulated dataset, with 6 covariates, and I'm running into some results I do not understand. I constructed an example from my simulation code, where I fit a coxph model without frailty (M1) and with frailty (M2) on a number of data samples with a varying degree of heterogeneity (I'm running R 2.3.1, running takes ~1 min).

Dear List, I am trying to estimate a 3 dimensional density through the DPpackage. For example # model sigma <- matrix(c(0.1,0.05,0.05,0.05,0.1,0.05,0.05,0.05,0.1), ncol=3) rnormm<- rmvnorm(n=100, mean=c(5,100,150), sigma=sigma) sigma2 <- matrix(c(10,0.05,0.05,0.05,10,0.05,0.05,0.05,10), ncol=3) rnormm2<- rmvnorm(n=100, mean=c(20,1,110), sigma=sigma) rnormm<-rbind(rnormm,rnormm2)

Greetings, I am using library(survey) to analyze some complex sample data. After fitting a model I tried to use termplot() with make.panel.svysmooth(), but I received an error (see below). Could someone help me interpret the error message so I can make the necessary corrections? The make.panel.svysmooth() function seems to work fine, and termplot() worked fine after I dropped the smoother.

Hi Everyone, I have been trying to read some Arrayvision files( 2 channel cDNA) and am having some problem. My code is : setwd('C:/work/data/limma/ndd1'); files <- c('ndd1_1.txt','ndd1_2.txt','ndd1_3.txt'); RG=read.maimages(files,"arrayvision",sep="\t"); #Normalisation MA=normalizeWithinArrays(RG); #plotPrintTipLoess(MA); #Fit Linear

Hi Samba Team, We are currently running on Samba 2.2.3a version. As part of the technology upgrade, management is willing to upgrade the current samba versions of in production machines. Can you please tell me how long I can use the 2.2.3a version? And if you suggest me to upgrade to a higher version, which version will best suite for us ?. Thanks in Advance.....Hisham Unless expressly stated

Hi There I have a lm object with 4 parameters and I want to test wether 2 parameters are equal using a Wald test (basically b1=b2 or b1-b2 =0). In the help file from R it says that under ANOVA the optional arguments " Terms" or "L" test whether a linear combination is equal to 0. I tried; >anova(m1, Terms = Beta1-Beta2=0) but I get the error: Object " Beta1"

Hello: I am new to R Help so hopefully I will have included enough information to allow for valuable feedback on an error message I am receiving. I am trying to a fit a mixed effects cox model to binary elk telemetry data to look at movement decisions relative to other possibilities (specifically selection or avoidance of risk <- kauf_avg ) in a matched-case-control framework. >

I am using R to teach, and here are a couple of things that I thought would work didn't work. 1. I noticed the utility data(***,package=***) recently and like it very much, but unless I type in the whole word "package" I'll get an error in 1.4.0. For example, data(cats,package=MASS) works fine but data(cats,pac=MASS) doesn't. 2. drop1 doesn't seem to be as smart as

I installed the locfit package under Linux (gcc 2.7.2). Installation was ok but > x <- runif(200) > y.compl <- 10*x*x*rgamma(200,3) > med.y <- median(y.compl) > cens <- ifelse(y.compl<=med.y,1,0) > y <- cens * y.compl + (1-cens)*med.y > library(locfit) > m <- locfit(y~x,cens=cens,family="gamma") /usr/local/src/R-0.61.1/bin/R.binary: can't

I have a parameter vector, ibeta, and a corresponding vector of loglikelihoods, llbet. If llbet contains no NAs or Inf's then I can extract the best parameter by index <- order(-llbet)[1] beta <- ibeta[index] or similar. The argument na.last of order() allows me to fix this up even if llbet contains some NAs which I wish to ignore. Unfortunately my llbet contains Inf's, which

Hi -- I'm trying to package R for inclusion on some upcoming Red Hat Powertools distribution. I have started with the 0.61 version packaged by Martyn Plummer <plummer at iarc.fr> (Thanks Martyn!) and have upgraded to 0.62-2. I have succeeded in running R demo's on i386-redhat-linux-gnu, and now I am also trying to get the alpha and sparc versions working. On sparc-redhat-linux,

I was wondering if someone could help me with a problem getting locfit running. I am running Digital Unix 3.2D on an alphastation, with R 0.61.1 I downloaded the CRAN distribution of locfit. I had no problems installing it with R INSTALL (I installed it into my library rather than the default base library; the output is attached at the end of this email message). I then tried to test it with the

In what way is this a bug in R? It looks like a bug in the package, and as Defn.h is not part of R's API any packge using it is `at risk' (and cannot be installed in a binary-only installation, or even an installed version of R). In particular, Defn,.h depends on config.h, and it seems you installed a binary version of R and used separate sources. I would suggest building R from

Full_Name: Richard Boyce Version: 2.1.-1 OS: Debian testing/unstable Submission from: (NULL) (128.95.123.29) While building a custom package using a modified version of Duncan's REventLoop with R version 2.1 (Debian package r-base, r-base-dev) and R source from apt-get source 2.1.1 I get the following error: $ R CMD build vjREventLoop * checking for file