[R] 'stretching' a binomial variable

Hi, Im carrying out some Bayesian analysis using a binomial response variable (proportion: 0 to 1), but most of my observations have a value of 0 and many have very small values (i.e. 0.001). I'm having troubles getting my MCMC algorithm to converge, so I have decided to try normalising my

Re: [R] GeoR model.control - defining covariates at prediction locations

P.J. Date: Mon, 18 Aug 2008 02:59:50 -0700 (PDT) From: imicola [EMAIL PROTECTED] Subject: [R] GeoR model.control - defining covariates at prediction locations To: r-help@r-project.org Message-ID: [EMAIL PROTECTED] Content-Type: text/plain; charset=us-ascii Hi, Im using

[R] Coordinate systems for geostatistics in R

Hi, I read somewhere that when carrying out geostatistical analysis in R you should not use latitude and longitude...can anyone expand on this a little for me, and what would be the best coordinate system to use? I have my data in a geographic coordinate system, WGS84, decimal degreesis

[R] GeoR model.control - defining covariates at prediction locations

Hi, Im using geoR and I'm trying to do some predictions, based on an external trend. I'm having some problems specifying my model.control, specifically how do I define my model, and also the source of the covariate data at the prediction locations? I am assuming that the covariate data at the

[R] Geodata object border

Sorry, this is probably quite an easy question, but I'm new to R and couldn't find the answer anywhere. I'm using geoR and geoRglm, but can't figure out how to get a border in my geodata object. Does this need to be defined when I'm importing my data, or afterwards, and how do I go about doing