similar to: Covariable Logistic Regression In R

Thank you so much David, here is correction: d1=suppressWarnings(read.csv("/Users/anamaria/Downloads/B1.csv", stringsAsFactors=FALSE, header=TRUE)) d1$X <- NULL d2=as.matrix(sapply(d1, as.numeric)) pdf("~/graph.pdf") b<-barplot(d2, legend= c("SYCL", "CUDA"), beside= TRUE,las=2,cex.axis=0.7,cex.names=0.7,ylim=c(0,80), col=c("#9e9ac8",

Hello, I have a data frame like this: d11=suppressWarnings(read.csv("/Users/anamaria/Downloads/B1.csv", stringsAsFactors=FALSE, header=TRUE)) > d11 X Domain.decomp. DD.com..load Neighbor.search Launch.PP.GPU.ops. Comm..coord. 1 SYCL 2. 1 0 3.7 0. 1 1 .6 2 CUDA 2 0 3. 1 0 1 .0

Dear R users. I'm trying to fit a generalised linear spatial mode using the geoRglm package. To do so, I'm preparing my data (geodata) as follow: geoData9093 = as.geodata(data9093, coords.col= 17:18, data.col=15,* covar.col=16*) where covar.col is a factor variable (years in this case 90-91-92-93)). Then I run the model as follow: / model.5 = list(cov.pars=c(1,1),

This is problem 1 of 3 problems we are having with live migration and/or ACPI on Xen-4.3 and Xen-4.2. Any help would be appreciated. Detailed description of problem: We are using Xen-4.3-rc1 with dom0 running Ubuntu Precise and 3.5.0-23-generic kernel, and domU running Ubuntu Precise (12.04) cloud images running 3.2.0-39-virtual. We are using the xl.conf below on qemu-upstream-dm and HVM and

Hello, I am trying to find a hessian matrix that involves log(gamma(1/p)) second derivative, p being one of the parameters of the function. I am using a function "deriv" with the hessian=TRUE option, but psigamma is not on the list of derivative functions. I know that it is possible to use 'psigamma(p,deriv)', but it doesn't work with 1/p. Does anybody can help with this?

Hi, I have a data frame like this: > dput(df) structure(list(ID = 1:8, Type = c("gmx mdrun -ntmpi 8 -ntomp 1 -s benchPEP.tpr -nsteps 10000 -resethway", "gmx mdrun -ntmpi 8 -ntomp 1 -s benchPEP.tpr -nsteps 10000 -resethway", "gmx mdrun -ntmpi 8 -s benchPEP.tpr -nsteps 4000 -resetstep 3000", "gmx mdrun -ntmpi 8 -s benchPEP.tpr -nsteps 4000 -resetstep

Hello. My name is Ana. I?m doing an eology master, and I?m just learning how R works. I have a Mac OS X 10.5.6, and I?m tryng to run just a simple ANOVA nanalyses. I dowloaded R version 2.10.0, and it seems I have problems with the script. I don?t know what to do, I?ve already change the languages, be sure of being working in the correct directory and doesn?t work the script is: #1. example

I have code like this: data <- read.csv("test1.csv", stringsAsFactors=FALSE, header=TRUE) # Graph myplot=ggplot(data, aes(fill=condition, y=value, x=condition)) + geom_bar(position="dodge", stat="identity", width=0.5) + scale_fill_manual(values=c("#7b3294", "#c2a5cf", "#a6dba0", "#008837"))+

Dear R developers: I am a PHD candidate student in the school of public health of Peking University and my major is genetic epidemiology. I am learning the FAM-MDR algorithm, which is used to detect the gene-gene and gene-environment interactions in the data of pedigree. The codes were written by Tom Cattaert of the University of Liege. The algorithms and the sample datasets are available at

Hi, all, I am new to R or even to statistics. Not sure if the question has a answer. But I couldn't find a straight forward answer in the help mailing list. I need use MicroArray data to select several diagnostic genes between Normal samples and Tumor samples and use these genes to predict unknow samples. Since the sample size is so small and data doesn't follow normal distribution, I am

I am looking for R packages that can make a Logistic Regression model with parameter estimation by Maximum Likelihood Estimation. Many thanks for helping out.

Hola a todos, Acudo a vosotros después de darle muchas vueltas al tema en Internet y no localizar la solución para algo que creo trivial. Necesito aplicar el test de Quade a un conjunto de datos en el que existe más de una covariable. El ejemplo de dicho test en R es el siguiente: ## Conover (1999, p. 375f): ## Numbers of five brands of a new hand lotion sold in seven stores ## during one week. y

Hello, Despite my search, I didn't find a post-hoc test for an ANCOVA. I used the functions aov() and lm() to run the ANCOVA then I tried TukeyHSD() but it didn't work (because of the covariable is a continuous variable?). Furthermore, I would like to plot the adjusted values (i.e. the values of the tested variable taking into account the covariable). Thanks for your help! N. Poulet

CRAN (and crantastic) updates this week New packages ------------ * apcluster (1.0.1) Ulrich Bodenhofer http://crantastic.org/packages/apcluster The apcluster package implements Frey's and Dueck's Affinity Propagation clustering in R. The algorithms are analogous to the Matlab code published by Frey and Dueck. * BioPhysConnectoR (1.6-1) Franziska Hoffgaard

Tengo un modelo de regresión de Cox y quiero obtener el plot ajustado por una covariable (sexo) con la función ?ggadjustedcurves?, pero me da el siguiente error: > cox2 <- coxph(os ~ imc_25 + sexo.1, data = datos) > cox2 Call: coxph(formula = os ~ imc_25 + sexo.1, data = datos) coef exp(coef) se(coef) z p imc_25 -0.621 0.537 0.299 -2.08 0.038 sexo.1M 0.714

Hola, # Hacemos el KED. Ver función "krige()": KED.rad <- krige( formula=pluvPcp~layer, # covariable -> radar locations=lluvia.rad.pluv.spdf, newdata=radarGrid, # podría ser cualquier objeto Spatial model=v.fit, # modelo de semivariograma. maxdist=Inf

Hello and thanks in advance for any help, I am using the 'multinom' function from the nnet package to calculate a multinomial logistic regression. I would like to get a matrix estimates of the estimated coefficient variances and covariances. Am I missing some easy way to extract these? Grant [[alternative HTML version deleted]]

Hello I'm trying to write a model for my data, but Im not sure it's statistically correct. I have one variable (2 levels: A or B). To explain it, I've got 2 factors and 3 continuous variables. I need to do a logistic regression, but... First: can I actually do a logistic regression with all of this? I know it's a basic question (sorry) but I just cant find a clear answer.

Hi all! I am trying to develop a plot a figure in which I would like to show the odds ratios obtained from a logistic model. I have tried with the dotplot option but no success. Could you help me? Is there any option when modelling the logistic model in R? Thank you in advance

Dear R-users I analysed the same data set by two different ways; analysis of covariance by using lm and anova functions and multiple comparison by using simtest function in the multcomp library. The output from the analysis of covariance is; > y<-lm(D~Cond+Q1,data=x) > anova(y) Analysis of Variance Table Response: D Df Sum Sq Mean Sq F value Pr(>F) Cond 2