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Dear R users; Im working with lme and Id like to have an idea of how can I get CI for the predictions made with the model. Im not a stats guy but, if Im not wrong, the CIs should be different if Im predicting a new data point or a new group. Ive been searching through the web and in help-lists with no luck. I know this topic had been asked before but without replies. Can anyone give an idea of

Hello R Experts, I started to work with the qcc package and it wprks quite nicely. Heres My Code: n <- c(55,5,94,25,10,15,15,40,44,34,90,114,204,37,30,28,12,68,64,29,24,14,31,16,62,45,55,20,24,14,9,19,76,57,55,42,6, 54,32,117,19,32,9,11,13,31,27,33,44,28) x <- c(6,0,30,5,2,1,4,5,2,9,12,24,64,3,9,21,9,48,15,4,3,0,1,0,6, 7,2,0,3,2,0,5,1,2,6,9,1,6,2,0,1,4,8,0,1,1,3,0,0,0)

violating.runs I read from the news cran.r-project.org/doc/Rnews/Rnews_2004-1.pdf that the criteria for the violating is 5 but 1)I cannot find "5" in the code of the function. Where is the "5" ? 2)What is the easiest way to change it ? 3)Is there any more criterias made somewhere ? Yours sincerelly, Tommi Viitanen

I have windows version of R v1.6.2 I have downloaded the qtoolbox.zip from http://www.cmis.csiro.au/S-PLUS/qtoolbox/ My R command line is > install.packages("C:/Program Files/R/qtoolbox.zip", .libPaths()[1], CRAN = NULL) and I get the following error message: updating HTML package descriptions Warning message: error -1 in extracting from zip file > Is there another way to

...you to do the thinking. When the ratio of the largest to smallest observation is large you should question whether the data are being analyzed in the right metric (transformation) . Original data should be presented in a way that will preserve the evidence in the original data. (W. A. Shewhart) You can see a lot by just looking. (Yogi Berra) A computer should make both calculations and graphs. Both sorts of output should be studied; each will contribute to understanding. (F.J. Anscombe) Murphy works hard to ensure that anything that can go wrong will go wrong. With an ad...