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2017 Jun 18
0
R_using non linear regression with constraints
...per = c(3000,1)) summary(myfit) library(nlsr) r <- 2 myfitj=nlxb(y~a*b*(1-exp(-b*r*x)),data=mydata,start=list(a=2000,b=0.05), trace=TRUE) summary(myfitj) print(myfitj) myfitj2<-nlxb(y~ab*(1-exp(-b*r*x)),data=mydata,start=list(ab=2000*0.05,b=0.05), trace=TRUE) summary(myfitj2) print(myfitj2) myfitj2b<-nlxb(y~ab*(1-exp(-b*r*x)),data=mydata,start=list(ab=2000*0.05,b=0.05), trace=TRUE, upper=c(1000, Inf)) summary(myfitj2b) print(myfitj2b) # End of script # On 2017-06-18 01:29 PM, Bert Gunter wrote: > https://cran.r-project.org/web/views/Optimization.html > > (Cran...
2017 Jun 18
3
R_using non linear regression with constraints
https://cran.r-project.org/web/views/Optimization.html (Cran's optimization task view -- as always, you should search before posting) In general, nonlinear optimization with nonlinear constraints is hard, and the strategy used here (multiplying by a*b < 1000) may not work -- it introduces a discontinuity into the objective function, so gradient based methods may in particular be
2017 Jun 18
3
R_using non linear regression with constraints
...> myfitj=nlxb(y~a*b*(1-exp(-b*r*x)),data=mydata,start=list(a=2000,b=0.05), > trace=TRUE) > summary(myfitj) > print(myfitj) > > myfitj2<-nlxb(y~ab*(1-exp(-b*r*x)),data=mydata,start=list(ab=2000*0.05,b=0.05), > trace=TRUE) > summary(myfitj2) > print(myfitj2) > > myfitj2b<-nlxb(y~ab*(1-exp(-b*r*x)),data=mydata,start=list(ab=2000*0.05,b=0.05), > trace=TRUE, upper=c(1000, Inf)) > summary(myfitj2b) > print(myfitj2b) > # End of script # > > On 2017-06-18 01:29 PM, Bert Gunter wrote: >> https://cran.r-project.org/web/views/Optimi...
2017 Jun 18
0
R_using non linear regression with constraints
...a*b*(1-exp(-b*r*x)),data=mydata,start=list(a=2000,b=0.05), trace=TRUE) >> summary(myfitj) >> print(myfitj) >> >> myfitj2<-nlxb(y~ab*(1-exp(-b*r*x)),data=mydata,start=list(ab=2000*0.05,b=0.05), trace=TRUE) >> summary(myfitj2) >> print(myfitj2) >> >> myfitj2b<-nlxb(y~ab*(1-exp(-b*r*x)),data=mydata,start=list(ab=2000*0.05,b=0.05), >> trace=TRUE, upper=c(1000, Inf)) >> summary(myfitj2b) >> print(myfitj2b) >> # End of script # >> >> On 2017-06-18 01:29 PM, Bert Gunter wrote: >>> https://cran.r-...