similar to: define F-ratio computations with aov

Hi all, I' m trying to figure out if it is appropriate to do a PCA having only categorical data (not ordinal). I have only find the following quote: One method to find such relationships is to select appropriate variables and to view the data using a method like Principle Components Analysis (PCA) [4]. This approach gives us a clear picture of the data using KL-plot of the PCA. However, the

Hi there, I switched servers yesterday. The old server was running 2.2.7a-1 on RedHat 8.0. The new server is 3.0.8-0.pre1.3 on Fedora Core 3. I did the migration by copying the following: /etc/passwd /etc/group /etc/shadow /etc/samba/* I then copied /home and fixed all the permissions on stuff. I then started up samba on the new server, and unplugged the old one. Most everything went

Dear all, Suppose I have a nested, repeated measure lme model. Which of the following formulae is correct? (assuming data are sampled from several plots in an agricultural experiment) (1) y~explanatory.variables,random=~time|block/plot/subplot/individual (2) y~explanatory.variables,random=~time|unique.ID.of.every.individual I have read that (2) is the only approach that works. But how could I

Hello, Below is some example code that should reproduce an error I'm encountering while trying to create a tiff plot with two subplots. If I run just the following bit of code through the R GUI the result is what I'd like to have appear in the saved tiff image: x<-seq(0:20) y<-c(1,1,2,2,3,4,5,4,3,6,7,1,1,2,2,3,4,5,4,3,6) plot(x,y,type="l",las=1,ylim=c(0,12))

hi everybody, I noticed the following: in one of my scripts 'layout' is used to generate a (approx. square) grid of variable dimensions (depending on no. of input files). if the no. of subplots (grid cells) becomes moderately large (say > 9) I use a construct like ###layout grid computation and set up occurs here### ... opar <- par(no.readonly = T);

Hi everybody, I am trying to fit a model with the lmer function for mixed effects. I have an experimental design consisting of 5 field plots. Each plot is divided in 12 subplots where the influence of three factors on the growing of tree seedlings is tested: (1) seed (1 = presence; 0 = absence); (2) seedling species (oak holm vs. pine); (3) treatment (three different treatments). In each of

Hi everyone. I would like to make a graphic with 2 subplots (lets say A and B). For instance, I use : par(mfcol = c(2,1)); The 2 subplots use the same X axis. So I provide no tics labels and no xlab for the top plot. I would like the second plot to be right bellow the first one (small margin). So my question is how I can keep a small gap between the 2 plots while having enough space under

Hi all i have two data sets, spot and futures cash market prices. to estimate the minimum variance hedge ratio, i first had a glance on the correlation coefficient of relative price change (ln(St / St-1). surprizingly the value is just 0.2 compared to actual price correlation of 0.9. (i did regress the spot change on future change, co-effi is 0.3, and R2 is only 0.025 a) in such scenario can

(Sorry if this is a repost, I got a bounce reply from the r-help server) Hi, I’m using the biglm() function to create some linear models for a very large data set than lm() can’t fit due to memory issues (the problem is with the number of interactions, I can fit the main effects model) I need to determine if the 2-way interactions are necessary or not. Ideally I’d like to use anova() to

Hi all, I am trying to calculate the variance ratio of a time series under heteroskedasticity. So I know that the variance ratio should be calculated as a weighted average of autocorrelations. But I don't find the same results when I calculate the variance ratio manually and when I compute the M2 (M2 for heteroskedasticity) variance ratio using Lo.Mac function in R. Anybody knows what

Hello, I am looking for a code in R for the variance ratio test statistic (the Lo and Mackinlay version or any other versions). Does anybody have such a code they can share or know a library in which I can find this function? Basically I have a number of time series which I need to check for persistence. One other test I can use is the runs test in the tseries package. Any help will be greatly

Ms.Karunambigai M PhD Scholar Dept. of Biostatistics NIMHANS Bangalore India ----- Forwarded Message ---- From: karuna m <m_karuna2002@yahoo.com> To: R-help@r-project.org Sent: Thu, 26 May, 2011 10:55:02 AM Subject: likelihood ratio test Dear R-help, Can anybody tell me which R package has Lo-Mendell Rubin LR test and Bootstrap LR test to compare the model fit between k class and k+1

It seems to me that R returns the unpenalized log-likelihood for the ratio likelihood test when ridge regression Cox proportional model is implemented. Is this as expected? In the example below, if I am not mistaken, fit$loglik[2] is unpenalized log-likelihood for the final estimates of coefficients. I would expect to get the penalized log-likelihood. I would like to check if this is as expected.

I'm applying logistic regression to a moderate sized data set for which I believe Wald based confidence intervals on B coefficients are too conservative. Some of the literature recommends using confidence intervals based on the likelihood ratio in such cases, but I'm having difficulty locating a package that can do these. Any help would be immensely appreciated. Best, Jeff Hanna --

Dear all, I have a problem which I'm not sure if it is due to my machine or if I'm doing something wrong. I'm ploting a little map using plot(val, type="l", asp=1) where val is the object with the latitude/longitude data. In the screen the figure is perfect, and I can copy to the clipboard and paste it to other places. I can also saved using png() or jpeg(), althoug

Hello, I would like to get the likelihood ratio and score tests for specific variables in a multivariate coxph model. The default is Wald, so the tests for each separate variable is based on Wald's test. I have the other tests for the full model but I don't know how to get them for each variable. Any idea? David Biau. [[alternative HTML version deleted]]

-----Ursprüngliche Nachricht----- Von: Wildi Marc, wia Gesendet: Mittwoch, 18. August 2004 10:11 An: r-help@lists.R-project.org Betreff: Hi Does anybody know from an R-package devoted to sample selection problems (Heckman's lambda, Lewbel, ...)? Thanks and best regards Marc Wildi [[alternative HTML version deleted]]

After playing around I got everything to work. One problem was with the large pointsizes. I switched to small pointsizes and shrank the plot region. This shrank the gaps and tick lengths down to reasonable values. As for aspect ratio, I think the pty="s" did finally kick in somehow. In the old days this was not required; the dev.print width=, height= took care of that. Cheers, Bill

Dear R help members, I have constructed a bar plot using ggplot, where I am showing the number of particles in 10m depth bins (from 0-150m) by release area (3 different ones) and Model (also 3 different ones). My problem is that for each release area a different number of particles was released (say 35, 45 and 56). I now need to be able to show the number of particles in each depth bin

Dear all, I always encounter a crash when running hazard.ratio.plot from rms package with my predictor as a factor. It works fine when the predictor is a continous score. Anyone encounters this too? Is this a bug or something? Thanks, Lilian [[alternative HTML version deleted]]