search for: tastard

...I think my data require the use of the glmmPQL function but I do not know how to make the model selection. Since the AIC and log-likelihood are apparently meaningless, how can we select the parameters for a model and compare the models to find which one fits best the data? Thanks a lot Emmanuelle Tastard Emmanuelle TASTARD UMR 5174 'Evolution et Diversité Biologique' Université Paul Sabatier Bat 4R3 31062 TOULOUSE CEDEX 9 France tel : 05 61 55 67 59 [[alternative HTML version deleted]]

...ed^2)+I(yellow^2)+densite8+I(densite8^2)+freq8_4 +I(freq8_4^2), random=~1|num, quasibinomial); Does it mean that there is no individual effect or is my model not good (number of groups (individuals)=number of observations, is it possible?). Thank you by advance for your help Emmanuelle TASTARD Output model1 : Call: glm(formula = y ~ red * yellow + I(red^2) + I(yellow^2) + densite8 + I(densite8^2) + freq8_4 + I(freq8_4^2), family = quasibinomial) Deviance Residuals: Min 1Q Median 3Q Max -3.4978 -1.5396 -0.1700 0.5210 4.5302 Coefficients:...

...quot;nlme","nlsList", or "nls" Yet, according to “?glmmPQL”, glmmPQL gives an object of class lme: Value: A object of class '"lme"': see 'lmeObject'. What should I do to be able to compare my models? Thank you. Emmanuelle Emmanuelle TASTARD UMR 5174 'Evolution et Diversité Biologique' Université Paul Sabatier Bat 4R3 31062 TOULOUSE CEDEX 9 France tel : 05 61 55 67 59 [[alternative HTML version deleted]]

Can you help me interpret the output I get with "polymars"? I'd like to find a regression model to predict 2 dependent variables (then called Y1 and Y2) with 2 independent variables (then called X1 and X2). Here is the output: polymars(responses = data[, 13:14], predictors = data[, 2:3]) Model fitting 0/1 size RSS 1 RSS 2 GCV 1 1 1 0.2486744