similar to: How to optimize or build a better random forest?

Greetings, I am working in the sem package on a model with 3 exogenous variables (2 are nominal-categorical), and 4 endogenous, continuous variables. To use sem with the nominal variables, I created dummy variables. Now, in my sem output I have estimates for path coefficients for the relationship between each level of the nominal variables and the endogenous variables they are associated

Dear R users, I am using lmer combined with AIC model selection and averaging (in the MuMIn package) to try and assess how isotope values (which indicate diet) vary within a population of animals. I have multiple measures from individuals (variable 'Tattoo') and multiple individuals within social groups within 4 locations (A, B, C ,D) crucially I am interested if there are

Hi I would really appreciate some help with my code for coxme... My data set I'm interested in survival of animals after an experiment with 4 treatments, which was performed on males and females. I also have two random factors: Response variable: survival (death) Factor 1: treatment (4 levels) Factor 2: sex (male / female) Random effects 1: person nested within day (2 people did

Hello R experts I have two linear regressions for sexes (Male, Female, Unknown). All have a good correlation between body length (response variable) and head length (explanatory variable). I know it is not recommended, but for a good practical reason (the purpose of study is to find a single conversion factor from head length to body length), the regressions need to go through the origin (0

Am I correct in assuming that the output below essentially translates to "Males have a mean time that is significantly lower than Females"? Is this the correct way to interpret the fact that the coefficient is negative? Assume the variale sex is treated as a factor with Female =0 and Male=1. survmodel<-survreg(survobj~sex,data=data1, dist="weibull")

I have a process where I am creating a effects plot similar to the cowles effect example. I would like to add the point estimates to the effects plot, can someone show me the correct syntax. I have included the "R" effects example, so you can show me the correct syntax. Thanks mod.cowles <- glm(volunteer ~ sex + neuroticism*extraversion, data=Cowles, family=binomial)

Dear list members, I fitted a glm model (See output below). My outcome is death, and weight (continuous), ClutchSize (3-level factor), EggVolume (continuous), Sex (obviously 2-level factor), and SiblingCompetence (2-level factor) are my covariates. I'd like to obtain the odds of death for a range of Weights, EggVolumes, and different combinations of ClutchSize. I've tried using the

Dear R-Help, My problem/bug came to light,when fitting a linear model using stepwise selection. I'd started with the straightfoward command step(lm(y~., dataset)) This worked fine, but because this starts with all the possible explanatory variables, it results in a model with too many explanatory variables. Hence I wanted to start with just a constant and do forward selection, to get a

Hello All, I cant seem to do a trig regression in R. The equation is as follows : y = a+b*(sin((2*pi*x/360) - c))^2 a, b, c are coefs that I want. y, x are input vectors. The equation I put into R: lm(y ~ sin(2*pi*x/360)^2) This equation is missing the c and I dont get the right answer. Also, I dont know how to plot the lm over the x values instead of the indices. Any help is sincerely

Hello all, I recently installed rpy2 so that I could use R through Python. However, R was not recognized in the command line. So I decided to add it to the PATH variables. But it just doesnt work.... And what I mean by it doesnt work is : No matter what I type at the prompt in DOS- be it R, Rcmd, R CMD, Rscript- it is not recognized as a command. Path variables used : 1. %R_HOME% -->

Hello All, Does anyone know how to download historical LIBOR rates of different currencies into R? Or if anyone knows of a website that holds all this data...I only need up to january of 2000. Also, how can we make the row names the index of a plot (the names of the x values)? [[alternative HTML version deleted]]

Hi, I have a problem with the time formatting in R. I have entered time in the format "MM:SS.xyz" and R has automatically classified this as a factor, but I need it numerically. However when I use as.numeric() it gives me totally different numbers. Is there any way I can tell R to read thes input as a number? Thank you very much [[alternative HTML version deleted]]

This concerns whether p-values from lmer can be trusted. From simulations, it seems that lmer can produce very small, and probably spurious, p-values. I realize that lmer is not yet a finished product. Is it likely that the problem will be fixed in a future release of the lme4 package? Using simulated data for a quite standard mixed-model anova (a balanced two-way design; see code for the

Guys, I wrote to the finance mailing list earlier with my questions but was directed here. Sorry for the repeat. --------------- library(quantmod) .... now <- Sys.time() midnight <- strptime() # <---- I want to make this a static variable that will be equal to 12:00:00 am but I dont know what to put here. I keep getting NA for everything I do if(now == midnight) {

Hi, here are three results of random forest (version 4.0-1). The results seem to be more or less the same which is strange because I changed the classwt. I hoped that for example classwt=c(0.45,0.1,0.45) would result in fewer cases classified as class 2. Did I understand something wrong? Christian x1rf <- randomForest(x=as.data.frame(mfilters[cvtrain,]),

Hey everyone, I hope this finds you in good cheer. I just have a quick question: What is the function that outputs the p-value for correlation? cor(x,y) only provides the R value. I would like the p-value associated with it. Thank you all for your help! [[alternative HTML version deleted]]

Hi, I am trying to model a dataset with the response variable Y, which has 6 levels { Great, Greater, Greatest, Weak, Weaker, Weakest}, and predictor variables X, with continuous and factor variables using random forests in R. The variable Y acts like an ordinal variable, but I recoded it as factor variable. I ran a simulation and got OOB estimate of error rate 60%. I validated against some

Hi All, I am looking for a reference that explains how the randomForest function in the randomForest package uses the classwt parameter. Here: http://tolstoy.newcastle.edu.au/R/e4/help/08/05/12088.html Andy Liaw suggests not using classwt. And according to: http://r.789695.n4.nabble.com/R-help-with-RandomForest-classwt-option-td817149.html it has "not been implemented" as of 2007.

Hi, I'm trying to install RSQLite on R 2.14 Ubuntu 12.04 i686. The installation always gets stalled and ends up not working. I installed libsqlite3-dev but still no luck. Anyone know how to solve this? $ R CMD INSTALL RSQLite_0.11.1.tar.gz * installing to library ‘/home/ubuntu/R/i686-pc-linux-gnu-library/2.14’ * installing *source* package ‘RSQLite’ ... ** package ‘RSQLite’ successfully

Hello, I'm the maintainer of a syntax highlighting tool highlight.js[1]. Recently the Kaggle project has announced they wanted to sponsor the development of the R highlighting definition for it[2]. I wanted to drop a line about it here since I suspect this list has much more R programmers on it than our small discussion group :-). So if you're interested and don't mind touching a