similar to: R CMD check: building indices error

PTAk_1.1-1 ( Principal Tensor Analysis on k modes) has been released on CRAN A multiway method to decompose a tensor (array) of any order, as a generalisation of SVD also supporting non-identity metrics and penalisations. 2-way SVD with these extensions is also available. The package includes also some other multiway methods: PCAn (Tucker-n) and

PTAk_1.1-1 ( Principal Tensor Analysis on k modes) has been released on CRAN A multiway method to decompose a tensor (array) of any order, as a generalisation of SVD also supporting non-identity metrics and penalisations. 2-way SVD with these extensions is also available. The package includes also some other multiway methods: PCAn (Tucker-n) and

Is there such a function (like sas.get for S ...) to be able to convert a SAS dataset (PC one .sd2) to a dataframe or matrix in R? thanks -- Didier G. Leibovici didier at fmrib.ox.ac.uk +44 (0)1865 222 739 Image Analysis Group fax:+44 (0)1865 222 717 Oxford University, Centre For Functional Magnetic Resonance Imaging of the Brain (FMRIB), John Radcliffe Hospital,

Removing rows with NAs, using na.omit(), doesn't seem to be working for me. Dataset: > str ( ex10s ) 'data.frame': 2189576 obs. of 5 variables: $ LOPNR : int 58 58 58 58 64 64 64 64 64 64 ... $ DIAGNOS: Factor w/ 173 levels "F20","F200","F2000",..: 128 128 128 128 105 105 105 160 105 105 ... $ X_DATE : int 20060821 20061207 20080102 20090904

Hi guys, I need some help to analyzing my data. I start to describe my data: I have 21 matrices, every matrix on the rows has users and on columns has items, in my case films. Element of index (i, j) represent the rating expressed by user i about item j. I have a matrix for each of professions. An example of a this type of matrix is: item 1 item 2 item 3 item4 id

Hi all, I'm having some troubles with the Quantreg package. I am using R version 2.10.0, and have downloaded the most recent version of Quantreg (4.44) and SparseM (0.83 - required package). However, when I try to run an analysis (e.g. fit1<-rq(y~x, tau=0.5)) I get an error message saying that the function "rq" could not be found. I get the same message when I try to search

Hello All, Is there a way of producing an ANOVA table split into contrasts, thus showing the contrasts sums of squares and associated p-values? Thanks, Martin. Martin Hoyle, School of Life and Environmental Sciences, University of Nottingham, University Park, Nottingham, NG7 2RD, UK Webpage: http://myprofile.cos.com/martinhoyle

Hi all, Has anyone tested for FA in R? I need to seperate out the variance due to measurement error from variation between individuals (following Palmer & Strobeck 1986). Andy Higginson Animal Behaviour and Ecology Research Group School of Biology University of Nottingham NG7 2RD U.K. This message has been checked for viruses but the contents of an attachment may still contain

Dear R Users, I suppose this is a school boy question, but here it is anyway. I'm trying to re-create the residuals for a poisson GLM with simulated data; x<-rpois(1000,5) model<-glm(x~1,poisson) my.resids<-(log(x)- summary(model)$coefficients[1]) plot(my.resids,residuals(model)) This shows that my calculated residuals (my.resids) are not the same as residuals(model). p 65 of

I want to form a 3x3 crosstabulation for the signs of two vectors (i.e. Negative, Zero, Positive). The problem is that I am simulating the data so for some iterations one of the categories is absent. Thus the resulting table shrinks to 3x2. I want it to be 3x3 with zero column corresponding to the missing category. Moreover, I have tried but failed to give the dimension names. -- Sohail Chand

Hello R Users, I am investigating the basic use of the LME function, using the following example; Response is Weight, covariate is Age, random factor is Genotype model.lme <- lme (Weight~Age, random=~ 1|Genotype) After summary(model.lme), I find that the estimate of Age is 0.098 with p=0.758. I am comparing the above model with the AOV function; model.aov <- aov (Weight~Age + Genotype)

Dear All, I wonder if anyone can advise me as to whether there is a consensus as to how the effect size should be calculated from GLIM models in R for any specified significant main effect or interaction. In investigating the causes of variation in infection in wild animals, we have fitted 4-way GLIM models in R with negative binomial errors. These are then simplified using the STEP procedure,

I have a problem with embedding R into perl. I downloaded the interface program/module from omegahat.org, and I can't seem to understand how to use it. This is all done under Win NT 4.0. If anyone have any clue or any suggestions on how to interface R into perl, I would be greatful. Please email me with comments at racerdude911 at yahoo.com Thanks Scott

Dear All, I'm rather a beginner on nested ANOVAs, so here goes with my 2 questions; Qu 1: I'm modelling the number of galls on a leaf (the response variable) as a function of; the tree on which I find the leaf, the branch on which I find the leaf. Then, the tree and the branch are both random factors, and I'm quite happy that I should write; aov(galls~tree/branch +

I have a large dataset (~1 million rows) of three variables: ID (patient's name), DATE (of appointment) and DIAGNOSIS (given on that date). Patients may have been assigned more than one diagnosis at any one appointment - leading to two rows, same ID and DATE but different DIAGNOSIS. The diagnoses may change between appointments. I want to subset the data in two ways: - define groups

Dear Greg, Thanks for the new release. The decomposition of the SSQ is just what I need! Regards, Martin. Martin Hoyle, School of Life and Environmental Sciences, University of Nottingham, University Park, Nottingham, NG7 2RD, UK Webpage: http://myprofile.cos.com/martinhoyle >>> gregory_r_warnes at groton.pfizer.com 10/30/02 07:16PM >>> Version 0.7.3 of the gregmisc package

Hi Stuart, I often use this small function standardize <- function(x) ( x - mean(x, na.rm=T) ) / sqrt(var(x, na.rm=T)) to standardize variables. You should be able to use this to do what you want by splitting the data frame into sections based on the factor level, using standardize() to create a new variable in each section, then paste the data frame back together. Something like: #

(Many thanks to David Barron & Jonathan Baron for pointing me to 'recode' in the 'car' package). I think I've been told this before, but how do I search for a function/keyword in libraries I don't yet have installed? (ie. on the CRAN site I tried the search engines with "recode" etc., but didn't pick up the car package this way) Stuart Dr Stuart Leask

Hi all, You will find in attachment to this mail some benchmarks we made on Linux with pios over ZFS-DMU. There are some interesting things about ZFS tuning and some ideas for breaking a bottleneck we identified in DMU. Thomas LEIBOVICI CEA/DAM - Ile de France -------------- next part -------------- A non-text attachment was scrubbed... Name: ZFS_benchs_Linux.pdf Type: application/pdf Size:

I've tried installing wine using synaptic on ubuntu, also compiling form source and a couple of other ways but never get a ./wine/config file ? Any idea what I'm doing wrong? Thanks Jim -- Dr. Jim Maas james.maas@nottingham.ac.uk This message has been checked for viruses but the contents of an attachment may still contain software viruses, which could damage your computer system: