search for: jebyrn

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 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

This is a 'rather than re-invent the wheel' post. Has anyone out there re-written combn so that it can be parallelized - with multicore, snow, or otherwise? I have a job that requires large numbers of combinations, and rather than get all of the index values, then crank it through mclapply, I was wondering if there was a way to just do this natively within a function. Just curious.

Hey, all. I had a quick question about fitting new glm values and then looking at the error around them. I'm working with a glm using a Gamma distribution and a log link with two types of treatments. However, when I then look at the predicted values for each category, I find for the one that is close to 0, the error (using se.fit=T with predicted) actually makes it overlap 0.

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

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

Dear list, I am currently working with a rather large data set on body temperature regulation in wintering birds. My original model contains quite a few dependent variables, but I do not (of course) wish to keep them all in my final model. I've fitted the following model to the data: >

...ge a large dataset ? (Greg Snow) 35. Cox Proportional Odds Model (Steve Jaffe) 36. Code of the max() function (Paul Smith) 37. help_if command_new column (barbara horta e costa) 38. Java-R (andrea.spano at quantide.com) 39. Re: Hierarchical Diagram of Networks in sna or otherwise? (jebyrnes) 40. Re: help_if command_new column (David Winsemius) 41. Re: Surface for R outside of R (Francisco J. Zagmutt) 42. Producing a legend successfullly (Steve Murray) 43. Re: Code of the max() function (David Winsemius) 44. [R-pkgs] frontier 0.99 is NOT backward compatible (Arne Henn...

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,

Hello all. I'm currently working with mixed models, and have noticed a curious difference between the nlme and lmer packages. While I realize that model selection with mixed models is a tricky issue, the two packages currently produce different AIC scores for the same model, but they systematically differ by 2. In looking at the logLik values for each method, I find that they

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,

Quick question, as I attempt to learn R. For post-hoc tests 1) Is there an easy function that will take, say the results of tukeyHSD and create a grouping table. e.g., if I have treatments 1, 2, and 3, with 1 and 2 being statistically the same and 3 being different from both Group Treatment A 1 A 2 B 3 2) I've been stumbling over the proper syntax for simple effects for a tukeyHSD

Hey, all, I may just be missing something, but I'm trying to construct a temporal autoregression with an independant variable other than just what is happened at a previous point in time. So, the model structure would be something like y(t)=b0+b1*y(t-1)+b2*y(t-2)...+a*x(t) I'm even considering a model of y(t)=b0+b1*y(t-1)+b2*y(t-2)...+a1*x(t)+a2*x(t-1)... So, my data looks like

Hello! I'm trying to get the Structural Equation Modeling software AMOS to run on an Mac running OSX 10.6.8 with wine 1.2.3 from macports. I'm running the student trial version from http://amosdevelopment.com/download/. The install seemed to go fine, but now that I'm running it (wine AmosGraphicsCLI.exe) I keep getting errors. First an error pops up Error number:429 Source:

I'm currently using JAGS as my Bayesian program of choice due to working off of an older mac running OSX. I'd like to utilize some of the functions from R2WinBUGS, however. As such, I'm attempting to write something to go from coda output dumped by JAGS into the bugs object format - I've looked for functions that will convert from an mcmc object to a bugs object, but

I had a question about scan in R. For better code readability, I would like to have lines in the block of data to be scanned that are commented - not just lines that have a comment at the end. For example #age, weight, height 33,128,65 34,56,155 instead of having to do something like 33,128,65 #age, weight, height 34,56,155 Is this at all possible?

Hey, all. I'm working on a data set with a broken stick linear regression where I know one of the two slopes. It is a negative linear function until the line intersects with the x-axis, at which point it becomes 0. It is not a nonlinear asymptotic function, and, indeed, using negative exponential or logistic types of fits as an approximation has tended to lead to an under or

Hello, R-i-zens. I'm working on an data set with a factorial ANOVA that has a significant interaction. I'm interested in seeing whether the simple effects are different from 0, and I'm pondering how to do this. So, I have my.anova<-lm(response ~ trtA*trtB) The output for which gives me a number of coefficients and whether they are different from 0. However, I want the

I'm having the most curious error while using the sem package. For the model I'm working with, I keep getting the following error: Error in J[cbind(1:n, observed)] <- 1 : subscript out of bounds I''ve used debug=TRUE with sem, and there don't appear to be any problems with model - there are no latent variables in this model. The variables in the covariance matrix