# Back-transformation of Beta in geoR Classic List Threaded 2 messages Reply | Threaded
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## Back-transformation of Beta in geoR

 Hi: I am interested in back-transforming the mle of parameter Beta and its variance when the Lambda parameter of the Box-Cox transformation has been estimated and its estimate is not 0 nor 0.5. Is this back-transformation equivalent to simply averaging over a fine grid inside the polygon containing the predictions of, say krige.conv (given that geoR back-transform when kriging= predicting)? For example >alpha<-sum(krig.object\$pred)/N >salpha<-sum(sqrt(krig.object\$krige.var))/N where krig.object has been obtained by using a likfit object as argument in krige.control, and N is the number of nodes in the grid (a big number). The questions are, 1) is alpha aproximately equal to the back- transformation of the mle of Beta? 2) is salpha aproximately equal to the 'standard error' of the back-transformation of the mle of Beta? Ruben
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## Back-transformation of Beta in geoR

 Dear Ruben You don't want to do kriging here. I think the most simple solution is to this by simulation. Implicitly you are saying that beta is one-dimensional. You will find the mean and variance of the beta parameter from the output from the likfit function. mean(BCtransform(rnorm(2000, mean=outfromlikfit\$beta, sd=sqrt(outfromlikfit\$beta.var)),lambda = 0.72, inverse = TRUE)) gives what you want. Ole Ruben Roa wrote: >Hi: > >I am interested in back-transforming the mle of parameter Beta >and its variance when the Lambda parameter of the Box-Cox >transformation has been estimated and its estimate is not 0 nor >0.5. >Is this back-transformation equivalent to simply averaging over >a fine grid inside the polygon containing the predictions of, say >krige.conv (given that geoR back-transform when kriging= >predicting)? >For example >   > >>alpha<-sum(krig.object\$pred)/N >>salpha<-sum(sqrt(krig.object\$krige.var))/N >>     >> >where krig.object has been obtained by using a likfit >object as argument in krige.control, and N is the number of nodes >in the grid (a big number). >The questions are, >1) is alpha aproximately equal to the back- >transformation of the mle of Beta? >2) is salpha aproximately equal to the 'standard >error' of the back-transformation of the mle of Beta? > >Ruben > >_______________________________________________ >R-sig-Geo mailing list >R-sig-Geo at stat.math.ethz.ch >https://stat.ethz.ch/mailman/listinfo/r-sig-geo> > >   > -- Ole F. Christensen BiRC - Bioinformatics Research Center University of Aarhus