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2010 Apr 15
0
nlsList {nlme} - control arguments problem
...length(xy$x)) # generate vector for predicted y (y1) to evaluate against observed y for(cnt in 1:length(xy$x)){ y1[cnt]<- min.s + dplt.s*x[cnt] + dif.s*x[cnt]^p.s} #predicting y1 for values of y evl<-sum((xy$y-y1)^2) #sum of squares is function to minimize return(evl)} #optimizing oppar<-optim(c(min.s , dif.s , dplt.s , p.s),func1,method="L-BFGS-B", lower=cc(0.0,0.0,0.0,-10), control=list(maxit=2000,parscale=c(1e3,1e-5,1e3,1e-1))) #saving optimized parameters value<-c(oppar$par[1L],oppar$par[3L],oppar$par[2L],oppar$par[4L]) names(value) <- mCall[c("...