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Dear all I have undertaken some phylogenetic and non-phylogenetic regressions with gls() in nlme with single preictor variables. A p value is associated with the intercept (upper p value) and another with the predictor variable (lower). Which p value is important? What does it mean if the intercept p value is insignificant but the predictor is still significant? Thanks a lot, and sorry for my

Hi I get the following error when I try and get the AICc for a gls regression using qpcR: > AICc(gls1) Loading required package: nlme Error in n/(n - p - 1) : 'n' is missing My gls is like this: > gls1 Generalized least squares fit by REML Model: thercarnmax ~ therherbmax Data: NULL Log-restricted-likelihood: 2.328125 Coefficients: (Intercept) therherbmax 1.6441405

Hi Is it possible to use grofit to get the AIC of several (e.g. two) growth models and compare both these and model parameters? All I can get it to do so far is return parameters for a single model. Cheers Roland [[alternative HTML version deleted]]

Hi I'm trying to use ouch's hansen and brown functions but I get the error: > brown(logflatnodes,archotreeouch) Error in backsolve(l, x, k = k, upper.tri = upper.tri, transpose = transpose) : NA/NaN/Inf in foreign function call (arg 1) and with hansen also: Error in optim(par = c(sqrt.alpha, sigma), fn = function(par) { : function cannot be evaluated at initial parameters

Hi I'm trying to replicate Smith et al.'s (http://www.sciencemag.org/content/330/6008/1216.abstract) findings by fitting their Gompertz and logistic models to their data (given in their supplement). I'm doing this as I want to then apply the equations to my own data. Try as a might, I can't quite replicate them. Any thoughts why are much appreciated. I've tried contacting the