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To understand some functions about spatial point patterns in "spatstat" ,I should know some background about it, and the best way is to read the monograph, and "Statistical Analysis of Spatial Point Patterns" (2nd edt.) is a better choise. But I can not find it anywhere I can. Who can help me? Thank you! ----- unangu at gmail.com -- View this message in context:

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

R-packages leaps and subselect implement various methods of selecting best or good subsets of predictor variables for linear regression models, but they do not seem to be applicable to logistic regression models. Does anyone know of software for finding good subsets of predictor variables for linear regression models? Thanks. -Ben p.s., The leaps package references "Subset Selection

Yes: I have Tufte's monograph on my desk. (along with 4 statistics texts) Yes: I am not the biggest fan of PowerPoint. Yes: I am using R to generate charts, plots, trends, etc. I have to summarize them each week. When I consider how to organize this data my first thought is to generate an HTML file with links to the R-generated plots, which HTML file organizes the plots in the required

Dear all, my question might be a bit off-topic. Is there anything like a standard textbook on statistical programming? With that I don't mean anything like MASS, S Programming, Programming with Data, ... (no offense meant, they are fantastic books and each of those three helped me a great deal). Rather in the direction of the "Numerical Recipes" Series addressing how to implement

Dear R-Devel, I have had it in my mind for some time now that a Task View related to R and education might be a good thing. There are currently 19 Task Views, covering a broad spectrum of general topics for which R may be used. The homepage lists 64 books related to R, and several of them have accompanying packages on CRAN. There is a wiki and a host of contributed documentation. We also have a

Hi, is there any method for goodness of fit testing of an (as general as possible) univariate distribution with parameters estimated, for normal, exponential, gamma distributions, say (e.g. the corrected p-values for the Kolmogorov-Smirnov or Chi-squared with corresponding ML estimation method)? It seems that neither ks.test nor chisq.test handle estimated parameters. I am aware of function

Hi *, Firstly, thank you so much for your time to read my email. I am currently interested in how to use R to predict time series from models fitted by ARIMA. The package I used is basic stats package, and the method I used is predict.Arima. What I know is that ARIMA parameters are estimated by Kalman Filter, but I have difficulty in understanding how exactly maximum likelihood (ML) estimator

Dear list, I want to combine several plots in one graph. I did this: plot(a1); plot(a2, add=TRUE); ...plot(a5, add=TRUE) The problem is the more plot we put, the more complex the graph. Is there any way to label each line; or other way just to make sure I know which one which? Thank you for the help, Ilham [[alternative HTML version deleted]]

Can anyone advise me on some pratical papers or books On Gaussian Copulas? Anything in the genre of Copulas Dummies Would be a help. As simpe, and approachable with minimal pedantic style. Thanks, Neil -------------------------------------------------------- This information is being sent at the recipient's reques...{{dropped:16}}

Howdy, I looked at the references in the R and S-Plus literature to find a good introduction/reference to GLM. When I then went to Amazon it seemed to me that all the recommended books are out of print. Can anyone give me a recommendation which _available_ book to get? --Ragnar -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Dear colleagues, I've just come across a problem with the following command which is a part of the "metaOverview.R" code file provided as an monography- accompanying file at http://www.bioconductor.org/docs/mogr/metadata: ################################## R> hasChr <- eapply(GOTERM, function(x) + x[grep("chromosome", Term(x))]) Error in

Hi All, This is off topic, but we're drawing a blank here.. > In a presentation I'll be giving next week, I want to include a reference > to a good general text on computing sample sizes for standard experiments. > Can anyone recommend a good book to use for this purpose? > > Thanks, > > -Greg LEGAL NOTICE\ Unless expressly stated otherwise, this

Greetings! I am looking for advice regarding the best way to compare GAMMs. I know other model outputs return enough information for R's AIC, ANOVA, etc. commands to function, but this is not the case with GAMM unless one specifies the gam or lme portion. I know these parts of the gamm contain items that will facilitate comparisons between gamms. Is it correct to simply use these values

Dear All, I've got a problem with ks.test. I've two realy large vectors, that I'd like to test, but I get an overflow, and the p-value cannot be calculated: > length(genomesv) [1] 390025 > length(scopv) [1] 140002 > ks.test(genomesv, scopv) Two-sample Kolmogorov-Smirnov test data: genomesv and scopv D = 0.2081, p-value = NA alternative hypothesis: two.sided

Just thought I would mention that there is a new O'Reilly book out, "Developing Bioinformatics Computer Skills", which is ok, pretty superficial about some things but at least it lets you know what is happening and where. R gets a few pages in there, 394-396, mostly nice press and accurate except that Bill Venables (hi Bill) may be surprised to find out that he is a member of the

Dear R Expert   allow me to ask a quick qestion: I have a mean value of 6 and a SD of 3 describing my distribution. I would like to "convert" this distribution into a log normal distribution that would best describe it when resimulated using log normal distribution. Currently I am using another software to estimate the respective mean and SD on the log scale and the results are: 1.6667

NIST maintains a repository of Statistical Reference Datasets at http://www.itl.nist.gov/div898/strd/. I have been working through the datasets to compare R's results to their references with the hope that if all works well, this could become a validation package. All the linear regression datasets give results with some degree of accuracy except one. The NIST model includes 11 parameters,

I have posted a new version of my document on R. I have corrected a number of errors and moved much of the detailed material on data structures to follow the chapter on exploration of multivariate data. I have changed the name; it is now: Using R for Data Analysis and Graphics - An Introduction The new document lives at: wwwmaths.anu.edu.au/~johnm/r/usingR.pdf My web page has information

Dear R developers, recently I have written a wishlist bug report for nlme containing a patch that adds the variance function structure s2(v) = t1^2 + t2^2*v^2 where v denotes the variance covariate, s2(v) denotes the variance function evaluated at v, and t, t1 and t2 are the variance function coefficients. The covariate can also be the fitted response. The idea that the residual variance