similar to: question about se of predicted glm values

Quick question about the usage of glht. I'm working with a data set from an experiment where the response is bounded at 0 whose variance increases with the mean, and is continuous. A Gamma error distribution with a log link seemed like the logical choice, and so I've modeled it as such. However, when I use glht to look for differences between groups, I get significant

I have a slight conundrum. I'm attempting to write a scrip that will take a number of objects (lm, glm, and lmer) and return AIC scores and weights. I've run into 3 problems, and was wondering if anyone had any pointers. 1) is there any convenient way to extract the name of the objects? Simply, if I have a vector of objects c(my.lm, my.lmer) and I want to get a character

Dear R folk, First off I want to thank those of you who responded with comments for my R quick and dirty stats tutorial. They've been quite helpful, and I'm in the process of revising them. When it comes to repeated measures MANOVA, I'm in a bit of a bind, however. I'm beginning to see that all of the documentation is written for psychologists, who have a slightly

Greetings to all, First off, I want to thank you all for answering any nagging questions I've had over the past few days. I've been in the process of putting together A Quick and (Very) Dirty Intro to Doing Your Statistics in R (which I have posted to http://didemnid.ucdavis.edu/rtutorial.html ) in order to teach an R workshop for the graduate students in my department. This is a

A quick question that I've had only partial success in answering. I have a multivariate dataset, and would like to extract some simple univariate information from it grouped by treatments, etc. I am encountering two problems however Note: I am importing my data with my_data <- read.csv("/path/data.csv") 1) Scoping of unstack If I attempt sorted_data <- unstack(response,

Hey, all, I'm trying to construct a centroid plot using canonical values from a MANOVA. I know that from the summary.manova object you can get Eigenvalues, and the H and E matrices (from SS$Treatment and SS$Residuals), but I am at a loss to get the loadings for the canonical values, nor values for the centroid centers and radii. Is there a package that does this that I am just missing,

Hey, all. I'm looking for packages that are good at two things 1) Drawing directed graphs (i.e nodes and edges), both with single and double headed arrows, as well as allowing for differences in line width and solid versus dashed. Note: I've tried Rgraphviz here, but have run into some problems (which seem fixable and I may go with it in the end), and it doesn't satisfy need

I'm working on a program that loads several large data files. I'm using ddply (plyr is really awesome) but I want to minimize the amount of times a large data file is read in. One solution is to keep track of which data file is open with a global variable and then change the currently open data file globally as needed. However, I'm unclear on how to alter a global variable

We're pleased to announce a one day course covering static and dynamic graphics using R, ggplot and GGobi. The course will be held just before the JSM, on Saturday, 28 July 2007, in Salt Lake City. The course will be presented by Dianne Cook and Hadley Wickham. In the course you will learn: * How to build presentation quality static graphics using the R package, ggplot. We will cover plot

X is a matrix and F is a vector. F2 <- data.frame(cbind(X,F)) F2 V1 V2 V3 F 1 -0.250536332 -1.4755883 1.9580974 -2.136487 2 -0.009856084 0.4953269 0.5486092 -2.744482 3 -0.406962682 0.7729631 0.1861905 -2.891821 4 1.938780097 0.7469251 1.2537781 -1.212992 5 -0.332370358 1.1943637 0.7114278 -1.830441 modF<-formula(F ~ V1 + V2 + V3) #no error message

Hi I am looking for a function which is executing some code repeatedly, exactly like lapply() and sappl() are doing, but do not return anything as I am not interested in the return values. An example would be: > p <- data.frame(runif(10), runif(10), runif(10)) > lapply( p, function(ps) {x11(); plot(ps)} ) which results in three graphs and a printout: $runif.10. NULL $runif.10..1

Hi, I'm having trouble with the "which" or the "seq" function, I'm not sure. Here's an example : > lat=seq(1,2,by=0.1) > lat [1] 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 > which(lat==1) [1] 1 > which(lat==1.1) [1] 2 > which(lat==1.2) [1] 3 > which(lat==1.3) [1] 4 > which(lat==1.4) [1] 5 > which(lat==1.5) [1] 6 >

Hi R, Getting a strange result using ?apply. Please look into the below codes: > d=data.frame(a=c(1,2,3),b=c("A","B","C"),c=c(TRUE,FALSE,FALSE),d=c(T,F,F )) > class(d[,1]) [1] "numeric" > class(d[,2]) [1] "factor" > class(d[,3]) [1] "logical" > class(d[,4]) [1] "logical" >

I'm working with a few functions (e.g. do.base.descriptions in the netstat package) that, in addition to returning an object with variables I want to extract, also print output. There is no way to turn this default printing behavior off in many of the functions. Is there a blanket way to suppress such printing, say, within a loop or a ddply statement? Thanks! -Jarrett

Hi, I tried several settings by using the "family=gaussian" in "gl1ce", but none of them works. For the case "glm" can work. Here is the error message I got: > glm(Petal.Width~Sepal.Length+Sepal.Width+Petal.Length ,data=iris,family=gaussian()) > gl1ce(Petal.Width~Sepal.Length+Sepal.Width+Petal.Length ,data=iris,family=gaussian()) Error in eval(expr, envir,

Hello, I have a loop with probability computed from a logistic model like this: for (i in 1:300){ p[i]<-exp(-0.834+0.002*x[i]+0.023*z[i])/(1+exp(-0.834+0.002*x[i]+0.023 +z[i])) x and z generated from normal distribution. I get 300 different probabilities And I want to generate variables from bernulli distribution with P for every observation: T[i]<-rbinom(1,1,p[i]) But i get missing

I want to extra the part of the formula not including the response variable from an lm object. For example if the lm object ABx.lm was created by the call ABx.lm <- lm( y ~ A + B + x, ...) Then ACx.lm is saved as part of a workspace. I wish to extract "~ A + B + x". Later in my code I will fit another linear model of the form z ~ A + B + x for some other response variable z. I

I'm attempting to write a general function to implement Faraway's bootstrapping algorithm for mixed models with lmer, but have run into a curious problem. I'm comparing two models model.1<-lmer(Response ~ Treatment + (1|Trial), data=exp.data, method="ML") model.2<-lmer(Response ~ 1 + (1|Trial), data=exp.data, method="ML") When I attempt to update

I've been using sna to work with some networks, and am trying to visualize them easily. My networks are hierarchical (food webs). All of the layout engines I've tried with gplot don't seem to plot hierarchical networks, as one would using dot from graphviz. While I could do all of this by outputting to dotfiles and running it through graphviz, the graphics I get from R are much

Hello there, I got a small problem about logical calculation: we can get a sequene from a+b as below: > a<-c(1,2) > b<-c(3,4) > a+b [1] 4 6 but when the sequences are logical. (I want to get (True,False) && (True, True) ==> (True, False), but when I do as below. > e<-c(T,T) > f<-c(F,T) > e [1] TRUE TRUE > f [1] FALSE TRUE >