similar to: classification for huge datasets: SVM yields memory troubles

Dear R community, I am trying to resolve a discrepancy between the way SPSS and R handle 2-way, repeated measures ANOVA. An experiment was performed in which samples were drawn before and after treatment of four groups of subjects (control and disease states 1, 2 and 3). Each group contained five subjects. An experimental measurement was performed on each sample to yield a

Dear R community, In the excellent nlme package the default diagnostic plot graphs the innermost residuals against innermost fitted values. I recently fit a mixed-effects model in which there was a very clear positive linear trend in this plot. I inferred that this trend occurred because my fixed effect was a two-level factor, and my random effect was a 12-level factor. The negative residuals

expression() accepts multiple expressions as arguments, thus: plot(1:2, 1:2) legend("topleft", expression(y == a * x^b, "where "* paste(y=="wood; ", x=="dbh"))) Is there a way to do this when values are to be substituted for a and b? i.e., the first element of the legend argument to legend() becomes,

Consider the following analysis of a class experiment done as a Latin Square: > spinner <- gl(4,4,16,label=c("Murray","Angela","Shasha","Stephen")) > order <- gl(4,1,16) > treat <- scan() 1: 1 2 4 3 5: 4 3 1 2 9: 3 4 2 1 13: 2 1 3 4 17: Read 16 items > coin <-

I am puzzled by the warning message in the output below. It appears whether or not I fit the seasonal term (but the precise point of doing this was to fit what is effectively a second seasonal term). Is there some deep reason why AR parameters ("Warning message: some AR parameters were fixed: ...") should somehow intrude into the fitting of a model that has only MA terms? >

I propose the following enhancements and changes to plot.lm(), the most important of which is the addition of a Residuals vs Leverage plot. (1) A residual versus leverage plot has been added, available by specifying which = 5, and not included as one of the default plots. Contours of Cook's distance are included, by default at values of 0.5 and 1.0. The labeled points, if any, are those

I apologize if this question is not completely appropriate for this list. I have been using SAS for a while and am now in the process of learning some C and R as a part of my graduate studies. All of the statistical packages I have used generally yield p-values as a default output to standard procedures. This week I have been reading "Testing Precise Hypotheses" by J.O. Berger

The inst/doc directory of the DAAG package has 6 files coral551.spot, ... that are around 0.85 MB each. It would be useful to be able to zip then, but that as matters stand interferes with the use of the Sweave file that uses them to demonstrate input of expression array data that is in the "spot" format. They do not automatically get unzipped when required. I have checked that

You need to give the model formula that gave your output. There are two sources of variation (at least), within and between locations; though it looks as though your analysis may have tried to account for this (but if so, the terms are not laid out in a way that makes for ready interpretation. The design is such (two locations) that you do not have much of a check that effects are consistent over

The following is from version 1.6.2 of R under Windows, or 1.6.1 under Mac OSX/X11 > density(1) Error in if (!(lo <- min(hi, IQR(x)/1.34))) (lo <- hi) || (lo <- abs(x[1])) || : missing value where logical needed I am not sure how this should be handled. I encountered it in connection with densityplot(). In that connection, it might be enough to modify density() so that it

Dear r-help community, Thank you for your previous answers! Now I have strange behaviour of the lattice library funcitons. They do not draw graphics in the file when called from the script. I created the script file, called, for example, "a.R", containing the following library(lattice); trellis.device(device="png", filename="a.png",

Fisher is not the only person that it may be necessary to read 4 or 5 times. The same may be the case for side comments that Bill Venables is wont to make. Now to the parallel universe that I have in mind. I wonder whether the time is opportune for a list that focuses on "Statistical Methodology for R Users". The difference from other statistical methodology lists is that it will be

I came across a very cheap of the infamous blue book - The New S Language (1988). Is this book still relevant to modern S or R or am I wasting my time? -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the

Hello, While using the "plot" function against a model with a long formula, I get a garbled label in the bottom of the plot. It looks like there are two lines printed one over another, here's my example: http://pico.magnum2.pl/maciej/NodalInvolvement/MisclassificationRate?action=AttachFile&do=get&target=TwoFactorResiduals.png This was from using

hi all i am busy teaching a regression analysis course to second year science students. the course is fairly theoretical with all of the standard theorems and proofs... i would like to give the class a practical assignment as well. could you suggest a good problem and the location of the data set/s? it would be good if the data set has been analysed by a number of other people so that students

I've generated a version of the classic dotplot of the barley data with library(lattice) data(barley) trellis.device("postscript", color=TRUE, file="barley2x3.ps") old.settings <- trellis.par.get() trellis.par.set("background", list(col = "white")) lset(list(superpose.symbol=list(pch=c(19, 1, 25, 2, 15, 22, 23),

Hello, supposing that I have two or three clear categories for my data, lets say pet preferece across fish, cat, dog. Lets say most people rate their preference as being mostly one of the categories. I want to do pca on the data to see three 'groups' of people, one group for fish, one for cat and one for dog. I would like to see the odd person who likes both or all three in the

I have a commonly recurring problem and wondered if folks would share tips. I routinely get tab-delimited text files that I need to read in. In very many cases, I get: > a <- read.table('junk.txt.txt',header=T,skip=10,sep="\t") Error in scan(file = file, what = what, sep = sep, quote = quote, dec = dec, : line 67 did not have 88 elements I am typically able to go

I have posted, at http://wwwmaths.anu.edu.au/~john/r/newsets/ image (.rda) files, and first stabs at .Rd files for various data on deaths in London from 1629 to 1939. (There are of course gaps.) The sources (Guy 1882 & Stocks 1942) are documented in the .Rd files: (1) poxetc: measles, smallpox & total deaths: 1629-1881 [I have deliberately left several inconsistencies that were in

As some of you R-devel readers may know, the plot() method for "lm" objects is based in large parts on contributions by John Maindonald, subsequently "massaged" by me and other R-core members. In the statistics litterature on applied regression, people have had diverse oppinions on what (and how many!) plots should be used for goodness-of-fit / residual diagnostics, and to my