search for: intersci

...E : andrewr at uidaho.edu PO Box 441133 W : http://www.uidaho.edu/~andrewr Moscow ID 83843 Or: http://www.biometrics.uidaho.edu No statement above necessarily represents my employer's opinion. Cited: Ripley, B.D. 1987. Stochastic Simulation. Wiley-Interscience; ______________________________________________ R-help at stat.math.ethz.ch mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html

Can someone recommend a more sophisticated way to annotate heatmaps than the ColSideColors argument of heatmap and heatmap.2? In particular, I would like to be able to annotate columns with more than one piece of information, like in Figure 1 of the article at http://www3.interscience.wiley.com/cgi-bin/fulltext/117905619/HTMLSTART / doi:10.1002/hep.22256. Some example data and a heatmap: set.seed(1) y <- matrix(rnorm(100),nrow=20,ncol=5) colnames(x) <- LETTERS[1:5] rownames(x) <- paste("r",1:20,sep="") set.seed(1) annotation <- matrix(sample...

Hello, I looked for R packages which focused on order-restricted statistical inference, but I could find only the isoreg() function. I would need to test whether the means in my (repeated measures) data follow a given order, e.g. A<B=C<D. I took a look at the monograph by Barlow et al. (1972) on this topic and found that for my case the null hypothesis is always A=B=C=D. This might be

I have a pretty big similarity matrix (2870x2870). I will produce even bigger ones soon. I am using PAM to generate clusters. The desired number of output clusters is a PAM input parameter. I do not know a-priopri what is the best clusters layout . I resorted to the silhouette test. It takes forever as I have to run PAM with all possible numbers of clusters. I wonder whether there is some faster

Users of R-Help might be interested in this new article by Bob O'Hara and Johan Kotze published on Methods in Ecology and Evolution on why you should not log-transform count data, including an R code: http://www3.interscience.wiley.com/journal/123328987/abstract Thanks Kind regards, Graziella ----------------------------------------------- Dr Graziella Iossa Journal Coordinator Methods in Ecology and Evolution Tel. +44(0)207 685 2518 Fax +44(0)207 685 2501 Email coordinator@methodsinecologyandevolution.org Web h...

R users doing data analysis may be interested in the following paper: http://methodsblog.wordpress.com/2009/11/13/first-paper-now-online/?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+wordpress%2Fmethodsblog+(methods.blog) All data and R code is available. Alain ----- -------------------------------------------------------------------- Dr. Alain F. Zuur First author of:

The standard chisq.test() and fisher.test() functions, when applied to two distributions (to determine whether the same underlying distribution applies to both) requires one to pre-bin the distributions. Is there a library function (either built-in or in a package) that acts more like the ks.test() function, in that one can simply pass the two distributions and have it do the necessary binning as

Dear all, I'm a beginner of R and I need to carry out some three-way mixed ANOVAs. Following examples at http://personality-project.org/r/r.anova.html, I managed to get the ANOVA part, but I don't know how can I check data normality and homogeneity of variance in R (since they're the required assumptions of ANOVA analysis). Are there any special command/packages? Could anyone give me

Hi, I am looking at the effects of two explanatory variables on chlorophyll. The data are an annual time-series (so are autocorrelated) and the relationships are non-linear. I want to account for autocorrelation in my model. The model I am trying to use is this: Library(mgcv) gam1 <-gam(Chl~s(wintersecchi)+s(SST),family=gaussian, na.action=na.omit, correlation=corAR1(form =~

Hello, I have been searching for ways to obtain these for combinations of fixed factors and levels other than the 'baseline' group (contrasts coded all 0's) from a mixed-effects model in lme. I've modelled the continuous variable y as a function of a continuous covariate x, and fixed factors A, B, and C. The fixed factors have two levels each and I'd like to know whether

Is there a way to get a reference list of journal articles that have used R? I am just looking for some examples of R graphs and presentation of results where R was used to generate the results. Thanks for any feedback and insights.

I am looking for a book that discusses the theory of multiple imputation (and other methods of dealing with missing data) and, just as importantly, how to implement these methods in R or S-Plus. Ideally, the book would have a structure similar to Faraway (Regression), Pinheiro&Bates (Mixed Effects) and Wood (GAMs) and would be very modern (i.e. published within the last couple of years).

Dear WizaRds, This is mostly a statistics question, but I'm figuring that R is the right solution (even before I start!) I have some bio data of heart rate versus time (rats taken from resting to maximal heart rate). I want to regress heart rate on time. The data have been normalized such that resting heart rate is zero at time=0, so that all curves intersect at the origin (and at the origin

hi to all, frustated for this error, to day i buy a 1 GB memory slot for my laptop now it have 1,28GB instead the old 512, but i've the same error :-( damn!damn!....how can i do? repeat for a little area (about 20X20 km and res=20m) it work fine! have you any suggestion? is ther a method for look if this error depend from my ram or other....? thanks foe any suggestion! i need your help.

Hi, I was wondering if I might be able to ask some advice about doing residual plots for the lmer function in the lme4 package. Our group's aim is to find if the expression staining of a particular gene in a sample (or "core") is related to the pathology of the core. To do this, we used the lmer function to perform a logistic mixed model below. I apologise in advance

I am sure there is something simple here I am missing, so please bear with me. It concerns the computation of the confidence interval for a population mean. The data are 125 measurements of Cs137 radation, a sample data set from Davis "Statistics and Data Analysis in Geology" 3rd ed. (CROATRAD.TXT) ------------------ method 1: using textbook definitions: mean \pm se_mean * t-value mu