pseudo R-squared with likfit (geoR)
... and you might also wish to try the R-sig-geo list, for obvious reasons. -- Bert On Wed, Nov 7, 2012 at 9:01 AM, Marion Jacquot
<marion.jacquot at univ-fcomte.fr> wrote:
We want to compute a pseudo R-squared for a model whose parameter estimation was based on maximum likelihood (function likfit, package geoR). I tried to compute the R2 proposed by Maddala (1983) which compare the maximized likelihood for the model without any predictor and the maximized likelihood for the model with all predictors. I got a really low value (0,01%). Did I miss something? Are there other R-squared which are more appropriate than the R2 of Maddala? :
>sp05_l01 <- likfit(cnm05g, *ini.cov.pars=vm05*, lik.method = "REML",
trend = trend.spatial(~ logIKA04 + nbLitre0 + nbLitre1, cnm05g))#complete model
>sp05_nt <- update(sp05_01, trend = trend.spatial("cte", cnm05g))
#null model
>1-(sp07_nt$loglik/sp07_l0$loglik)^(2/590)#Maddala (1983)
[1] 0.0001510074 Thanks, Regards, Marion -- Marion Jacquot Laboratoire de Chrono-environnement UMR UFC/CNRS 6249 USC INRA Universit? de Franche-Comt? Place Leclerc F-25030 Besan?on cedex FRANCE Tel. : +33 (0)381 665 829 Fax : +33 (0)381 665 797 http://chrono-environnement.univ-fcomte.fr/ [[alternative HTML version deleted]]
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Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm