search for: sumrys

I wrote a function which does "moving window" regressions. E.g. if there are 100 observations and the window width is 50, then I first run the regression for observations 1..50, then for 2..51, and so on. I am extremely pleased with R in my experience with writing this, since I was able to pass the model as an argument into the function :-) Forgive me if I sound naive, but that's

I suppose everybody who makes a package for the first time thinks "I can change anything!" and then runs into this same question. Has anybody written out information on how a package can override functions in R base in the R 2.14 (mandatory NAMESPACE era)? Suppose I want to alphabetize variables in a summary.data.frame, or return the standard deviation with the mean in summary output.

# Your mailer is set to "none" (default on Windows), # hence we cannot send the bug report directly from R. # Please copy the bug report (after finishing it) to # your favorite email program and send it to # # r-bugs@biostat.ku.dk # ###################################################### I stumbled on this error while doing a classroom demonstration. The error is reproducible,

I'm moving this part of an on-going discussion to r-devel because I think I've uncovered a bug: >summary.default : How is yours different from R's (I didn't try to find out) > If it has an advantage you should post to R-devel as a proposal I did propose it along time ago, but ... The fix was for a bug that Splus 3.2 and 3.3 have. It does not work properly with lists

Hello sir: Here's the result of repeated measures ANOVA. $"Error: Within" Df Sum Sq Mean Sq F value Pr(>F) t 2 524177 262089 258.24 1.514e-06 *** Residuals 6 6089 1015 --- Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 My question is: How to extract the F value only? If the result is a

Greetings. I've written a convenience function for multicollinearity diagnosis. I'd like to report to the user the formula that is used in a regression. I get output like this: > mcDiagnose(m1) [1] "The following auxiliary models are being estimated and returned in a list:" [1] "`x1` ~ ." formula(fmla)() [1] "`x2` ~ ." I'd like to fill in the period

Hi, I'm trying to use the library mclust for gaussian mixture on a numeric vector. The function Mclust(data,G=3) is working fine but the fitting is not optimal and is using modelNames="E". When I'm trying Mclust(data,G=3,modelName="V") I have the following message: Error in if (Sumry$G > 1) ans[c(orderedNames, "z")] else ans[orderedNames] : argument is

Hi, I'm trying to use the library mclust for gaussian mixture on a numeric vector. The function Mclust(data,G=3) is working fine but the fitting is not optimal and is using modelNames="E". When I'm trying Mclust(data,G=3,modelName="V") I have the following message: Error in if (Sumry$G > 1) ans[c(orderedNames, "z")] else ans[orderedNames] : argument is

I am looking for help to analyze an unbalanced AB/BA cross-over design by requesting the type III SS ! # Example 3.1 from S. Senn (1993). Cross-over Trials in Clinical Research outcome<-c(310,310,370,410,250,380,330,270,260,300,390,210,350,365,370,310,380,290,260,90,385,400,410,320,340,220) subject<-as.factor(c(1,4,6,7,10,11,14,1,4,6,7,10,11,14,2,3,5,9,12,13,2,3,5,9,12,13))

Hello, I have been trying to get an ANOVA table for a linear model containing a single nested factor, two fixed factors and a covariate: carbonmean<-lm(C.Mean~ Mean.richness + Diversity + Zoop + Diversity/Phyto + Zoop*Diversity/Phyto) where, *Mean.richness* is a covariate*, Zoop* is a categorical variable (the species), *Diversity* is a categorical variable (Low or High), and

Hello, I have been trying to get an ANOVA table for a linear model containing a single nested factor, two fixed factors and a covariate: carbonmean<-lm(C.Mean~ Mean.richness + Diversity + Zoop + Diversity/Phyto + Zoop*Diversity/Phyto) where, Mean.richness is a covariate, Zoop is a categorical variable (the species), Diversity is a categorical variable (Low or High), and Phyto (community

Hi all, I am a real novice to R. :) I am struggling with a problem for generating colored dendrogram. I have searched the R list and complied/collected a R code which can generated a colored dendrogram based on the rainbow color and 4x4 similarity matrix (say matrix:m). In this dendrogram, each leaf is colored differently. But, I do not want the leaf colored on a random basis. I want to assign