Hey, R users I am using numerical method for my research paper and the computation burden is very heavy. first I tried to do it with loops, example code as following, and it take hours to converge for only 200 obs. and my real data has 4000 obs. and the optimization command that I use is:
optim(guess,myfunc1,data=mydata, method="BFGS",hessian=T)) then I tried matrix form computation, it takes only 1/10 of the time the loop method takes. it may still have room to improve it. at least, the following part looks ugly. ccl[,m]<-lia[,1]*lia[,2]*lia[,3]*lia[,4]*lia[,5] any suggestion are appreciated. The Loop code: for(m in 1:ns){ for(i in 1:nt){ vbar2[,i]=a[1]+ eta[m]+acedu[,i]*a[2]+acwrk[,i]*a[3] vbar3[,i]=b[1]+b[2]*eta[m]+acedu[,i]*b[3]+acwrk[,i]*b[4] v8[,i]=1+exp(vbar2[,i])+exp(vbar3[,i]) for(j in 1:n){ if (edu[j,i]==1) lia[j,i]=1/v8[j,i] if (wrk[j,i]==1) lia[j,i]=exp(vbar2[j,i])/v8[j,i] if (home[j,i]==1) lia[j,i]=exp(vbar3[j,i])/v8[j,i] } ccl[,m]<-lia[,i]*ccl[,m] } } The Matrix code: for(m in 1:ns){ vbar2[,1:nt]=a[1]+ eta[m]+acedu[,1:nt]*a[2]+acwrk[,1:nt]*a[3] vbar3[,1:nt]=b[1]+b[2]*eta[m]+acedu[,1:nt]*b[3]+acwrk[,1:nt]*b[4] v8[,1:nt]=1+exp(vbar2[,1:nt])+exp(vbar3[,1:nt]) lia[1:n,]<-ifelse(edu[1:n,]==1,1/v8[1:n,], ifelse(wrk[1:n,]==1,exp(vbar2[1:n,])/v8[1:n,], exp(vbar3[1:n,])/v8[1:n,])) ccl[,m]<-lia[,1]*lia[,2]*lia[,3]*lia[,4]*lia[,5] } Nan from Montreal ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.