similar to: question in using nlme and lme4 for unbalanced data

Dear all, I am currently running an ENFA in R using Adehabitat pkg to assess species distribution and I am really stuck and need some help to finalize my project. I run the ENFA in both original location data and pseudo-absence points (the latter randomly generated using dismo pkg), and now I would like to assess the performance of the ENFA, however, I am not sure about how to tackle this. I

Dear All, I have a set of environental maps and presence-only points for some species. How can I generate distributions models on R using these presence-only data? What packages and functions can I use to do so? Kind regards, Miltinho Brazil [[alternative HTML version deleted]]

Dear all, I am running an Ecological Niche Factor Analysis in R but I am stuck with a problem. As soon as I ask the software to compute the ENFA, I get the following error message: Error in eigen(Se) : infinite or missing values in 'x' Does anyone know what could be wrong. I do not have missing values in my dataset. Please follow the codes I used for my analysis so far: library

Dear all, I have just uploaded to CRAN the version 1.4 of the package 'adehabitat'. Significant changes are listed below: - The eigenanalysis of selection ratios (Calenge and Dufour, 2006, Ecology) can now be performed using the function eisera(). It can be used for the analysis of habitat selection when habitat can be considered to consist of several habitat types (e.g.

Dear all, I have just uploaded to CRAN the version 1.4 of the package 'adehabitat'. Significant changes are listed below: - The eigenanalysis of selection ratios (Calenge and Dufour, 2006, Ecology) can now be performed using the function eisera(). It can be used for the analysis of habitat selection when habitat can be considered to consist of several habitat types (e.g.

Dear all, I have just uploaded a package to CRAN a new package called 'adehabitat'. This package is intended for ecologists who want to analyse the use of space by animals. Many functions currently used in this field are available to highlight habitat selection by animals (selection ratios, ENFA, habitat suitability maps with the algorithm DOMAIN or Resource Selection Functions) or to

Dear all, I have just uploaded a package to CRAN a new package called 'adehabitat'. This package is intended for ecologists who want to analyse the use of space by animals. Many functions currently used in this field are available to highlight habitat selection by animals (selection ratios, ENFA, habitat suitability maps with the algorithm DOMAIN or Resource Selection Functions) or to

Dear all, I have just uploaded to CRAN the version 1.2 of the package 'adehabitat'. This package now contains new functions for the estimation of home ranges (Nearest neighbour convex hull, brownian bridge approach for kernel estimation), estimation of schoener's ratio. This package now allows a better management of objects of class "area" (see plot.area, perarea, ararea).

Dear all, I have just uploaded to CRAN the version 1.3 of the package 'adehabitat'. Significant changes are listed below: - Several functions allowing the conversion from and to classes of the package sp have been added. Maps of class "asc", "kasc", "area", as well as radio-monitoring of class "traj" can now be converted to the spatial

Dear all, I have just uploaded to CRAN the version 1.3 of the package 'adehabitat'. Significant changes are listed below: - Several functions allowing the conversion from and to classes of the package sp have been added. Maps of class "asc", "kasc", "area", as well as radio-monitoring of class "traj" can now be converted to the spatial

Dear all, I have just uploaded to CRAN the version 1.5 of the package 'adehabitat'. Significant changes are listed below: * the package now contains a new function allowing a factorial decomposition of the Mahalanobis distances in habitat selection studies, named madifa(). * The ENFA can now be performed using all kinds of variables (numeric, factors, fuzzy, mixing of several types,

Dear all, I have just uploaded to CRAN the version 1.5 of the package 'adehabitat'. Significant changes are listed below: * the package now contains a new function allowing a factorial decomposition of the Mahalanobis distances in habitat selection studies, named madifa(). * The ENFA can now be performed using all kinds of variables (numeric, factors, fuzzy, mixing of several types,

Dear all, I have just uploaded to CRAN the version 1.2 of the package 'adehabitat'. This package now contains new functions for the estimation of home ranges (Nearest neighbour convex hull, brownian bridge approach for kernel estimation), estimation of schoener's ratio. This package now allows a better management of objects of class "area" (see plot.area, perarea, ararea).

Dear all, I have just uploaded to CRAN the version 1.6 of the package 'adehabitat'. Significant changes are listed below: * The package has been reorganized into four parts (see ?adehabitat-package for a description): (i) management of raster maps, (ii) habitat selection / ecological niche analysis, (iii) home range analysis, and (iv) analysis of animals trajects. The package contains

Dear all, I have just uploaded to CRAN the version 1.6 of the package 'adehabitat'. Significant changes are listed below: * The package has been reorganized into four parts (see ?adehabitat-package for a description): (i) management of raster maps, (ii) habitat selection / ecological niche analysis, (iii) home range analysis, and (iv) analysis of animals trajects. The package contains

Hi, I am using R to do a principal components analysis for a class which is generally using SPSS - so some of my question relates to SPSS output (and this might not be the right place). I have scoured the mailing list and the web but can't get a feel for this. It is annoying because they will be marking to the SPSS output. Basically I'm getting different values for the component

Hi I have a set of data with both quantitative and categorical predictors. After scaling of response variable, i looked for multicollinearity (VIF values) among the predictors and removed the predictors who were hinding some of the other significant predictors. I'm curious to know whether the predictors (who are not significant) while doing simple 'lm' will be involved in

Hi! I searched some time ago a way to get the Wilcoxon test results as a table more or less formatted. Nobody told me any solution and I found nothing on the Internet. Recently I came across this link ( http://myowelt.blogspot.com/2008/04/beautiful-correlation-tables-in-r.html), which helped me to find a solution. Here's the solution (I'm using R Commander): W <-

Hi, I am new to R (and not really a stats expert) and am having trouble interpreting its output. I am running a human learning experiment, with 6 scores per subject in both the pretest and the posttest. I believe I have fitted the correct model for my data- a mixed-effects design, with subject as a random factor and session (pre vs post) nested within group (trained vs control). I am

Dear community, I have a question regarding the standard error of "marginal hazard ratio" estimates from a cox proportional hazard model with an interaction term. I have to dichotomous variables ADMA and ALA (both low/high) where I have divided the continuous variables at a certain level. I am aware about the contra arguments categorizing a continous variable and I could as well use