"r.ghezzo" <[EMAIL PROTECTED]> writes: > Hello, I have a program with this section: > .. > for(i in 1:20){ > lo <- nls(y~y0+a/(1+(x/x0)^b),start=list(y0=0.1,a=a0,x0=x00,b=-8.1)) > beta[i] <- lo$m$getPars()[4] > } > .. > If the fit works this is OK but if the fit fails, the whole program > fails so: > .. > for(i in 1:20){ > try(lo <- > nls(y~y0+a/(1+(x/x0)^b),start=list(y0=0.1,a=a0,x0=x00,b=-8.1))) > beta[i] <- lo$m$getPars()[4] > } > .. > but the try catches the error in nls and beta[i] gets assigned > beta[i-1] from the previous loop. This is bad but no so bad as it can > be checked, > Now in some cases the error is in i=1 and the program stops!! > is there a way to set lo$m$getPars() to zero before the call? > I tried to understand the use of tryCatch() but frankly it is above > me. Sorry
Just check the return value from try: beta[i] <- if(inherits(try(.....),"try-error")) NA else lo$etc... (or use sapply) and, er, shouldn't there be a dependency on i somewhere in the model fit??? -- O__ ---- Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html