search for: nblitre0

I am working with the splm package. I use the spgm function: general estimation of a panel data model. Based on this approach, I know it is possible to compute a R2, eg the ratio of variation explained by a given model. My model is : bivmod<-spgm(logIKA~NBLITRE0+NBLITRE1,data=mydatap,listw=comsKnn.nbW,spatial.error=TRUE) I know that we can calculate the R^2 as the variance of the fitted values from the reduced form of the model (Yfitted) over the variance of y (here logIKA). Since I am using the option lag = FALSE; the fitted value for an error 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...