similar to: Error when using step

I posted this question way down at teh end of another thread realted to an error in step, but that was stupid since it really is another matter altogether. I should have posted it separately, as I have now done. The code below creates a data.frame comprising three marginally noisy surfaces. The code below (including a fix courtesy of David Winsemius that avoids a step function error through use

I have a large dataset grouped by a factor and I want to perform a regression on each data subset based on this factor. There are many ways to do this, posted here and elsewhere. I have tried several. However I found one method posted on the R wiki which works exactly as I want, and I like the elegance and simplicity of the solution, but I don't understand how it works. Its all in the formula

Dear Spencer and Prof. Fox, Thank you for your replies. I'll very appreciate, if you have any ideas concerning the problem described below. First, I'd like to describe the model in brief. In general I consider a model with three equations. First one is for annual GRP growth - in general it looks like: 1) GRP growth per capita = G(investment, migration, initial GRP per

Does anybody here have a suggestion for a clever way of creating contour plots for estimated bivariate density functions conditional on a factor? The contourplot function in the 'lattice' package only accepts data that are on the form 'z ~ x * y', not on the form 'x,y' or 'y~x'; otherwise I could probably have used the panel function to do the needed conversion.

I've setup dovecot to auth both system and virtual users but it is refusing to work. It keeps saying user is not found. Is there something more that I need to set? dovecot.conf: ============================================================================ = default_mail_env = maildir:/var/mail/%1.1u/%u/Maildir mail_extra_groups = mail protocol imap { } protocol pop3 { } protocol lda {

I am having great difficulty plotting what should be a simple graph. I have measured 1 'y' and 5 'x' variables in each of two groups. Linear regression shows significant differences in the slopes of the regression for each 'x' variable between the two groups. All that I want to do is to plot one graph that shows the scatterplot for the three groups (each group represented

Dear R helpers, I would like to ask why polr occasionally generates results that look very odd. I have been trying to compare the power of proportional odds logistic regression with the Wilcoxon test. I generated random samples, applied both tests and extracted and compared the p-values, thus:- library(MASS) c1=rep(NA,100); c2=c1 for (run in 1:100) { dat=c(rbinom(20,12,0.65),rbinom(20,12,0.35))

On F7, I get to where I have Postfix and Dovecot installed and configured, postfix check runs fine, but when I try to start Dovecot I'm getting a permission error. Here is the log entry: Dec 29 21:54:06 grp-01-50-90 dovecot: Dovecot v1.0.7 starting up Dec 29 21:54:06 grp-01-50-90 dovecot: Generating Diffie-Hellman parameters for the first time. This may take a while.. Dec 29 21:54:06

Summarization of the bug in Samba 3.0.2pre1: It seems that an ADS group is not valid or detected anymore to access a samba share, in case only an ADS group is used a valid user on a Samba share, because Kerberos is reporting: Username (null) is invalid on this system. Besides that, connecting to a share (service) reports with Samba 3.0.0-2 REALM\username (NH-TEST.NL\fo6), but with Samba 3.0.2pre1

Dear R experts, I would like to please ask for your help with repeating steps in an apply statement. I have a dataframe that lists multiple variables for a given id and visit, as well as drug treatment. > head(exp) id visit variable1 variable2 variable3 variable4 drug 1 3 1 13 10 7 11 0 2 3 5 10 15 9 9 0 3 3 12

Hi, I try to ask here, because I hope someone will help me understand this problem- I have fittet a glm in R with the results > glm1 <- > glm(log(claims)~log(sum)*as.factor(grp),family=gaussian(link="identity")) > summary(glm1) Call: glm(formula = log(claims) ~ log(sum) * as.factor(grp), family = gaussian(link = "identity")) Deviance Residuals: Min 1Q

Dear R-Helpers: I am using trying to use *ddply* to extract min and max of a particular column in a data.frame. I am using two different forms of the function: ## var_name_to_split is a string -- something like "var1" which is the name of a column in data.frame ddply( df, .(as.name(var_name_to_split)), function(x) c(min(x[ , 3] , max(x[ , 3]))) ## fails with an error - case 1 ddply(

1. I did not attempt to sort through your voluminous code. But I suspect you are trying to reinvent wheels. 2. I don't understand this: "I've failed to find a solution after much searching of various R related forums." A web search on "error handling in R" **immediately** brought up ?tryCatch, which I think is what you want. If not, you should probably explain why it

You can capture warnings by using withCallingHandlers. Here is an example, its help file has more information. dataList <- list( A = data.frame(y=c(TRUE,TRUE,TRUE,FALSE,FALSE), x=1:5), B = data.frame(y=c(TRUE,TRUE,FALSE,TRUE,FALSE), x=1:5), C = data.frame(y=c(FALSE,FALSE,TRUE,TRUE,TRUE), x=1:5)) withWarnings <- function(expr) { .warnings <- NULL # warning handler will

tryCatch() is good for catching errors but not so good for warnings, as it does not let you resume evaluating the expression that emitted the warning. withCallingHandlers(), with its companion invokeRestart(), lets you collect the warnings while letting the evaluation run to completion. Bill Dunlap TIBCO Software wdunlap tibco.com On Tue, Mar 6, 2018 at 2:45 PM, Bert Gunter <bgunter.4567 at

Dear R-helpers, the problem I'm facing today is to convince lattice to paint some areas in gray. The areas I would like to have in gray, are confidence bands I've googled around in the mailing list archives and eventually find some clues. This link is my starting point http://tolstoy.newcastle.edu.au/R/e2/help/07/04/15595.html I'm reproducing here the code for your convenience est

Hi, how can I get a more descriptive text instead of the variable names in my XY-lattice plot, according to the table below? Variable text acet = "Acetylaspartate Thalamus" chol = "Choline Thalamus" acetp = "Acetylaspartate parieoc" ino = "Inositole Thalamus" I could not find a solution. Please have a look at my syntax. Thanks a lot,

I have to fit a generalized linear model in R, and I have never done this before, so I'm in very much doubt. I have a dataset (of 4036 observations) claims sum grp 1 3852 34570293 1 2 1194 7776468 1 3 3916 26343305 1 4 1258 5502915 1 5 11594 711453346 1 ... there are 4 groups (grp). The task

Although this should be trivial, I'm having a spot of trouble. I want to make a lattice plot of the format y1+y2 ~ x | grp but then fit a lm to each y variable and add an abline of those models in different colors. If the xyplot followed y~x|grp I would write a panel function as below, but I'm unsure of how to do that with y1 and y2 without reshaping the data before hand. Thoughts

Hi everyone, I want to fit the following mixed effect model Y_ij = b_0i + b_1i * (t_ij*grp_ij == 1) + b_2i * (t_ij*grp_ij == 2) + v_0i + v_1i*t_ij + e_ij with a different covariance matrix of random effects for each group. (Y is the response t is time grp is the group indicator b 's are fixed effects v 's are random effects) I know that this is possible in SAS