Yuchen Luo wrote: > Dear Friends. > I found something very puzzling with constOptim(). When I change the > parameters for ConstrOptim, the error messages do not seem to be > consistent with each other: > > >> constrOptim(c(0.5,0.3,0.5), f=fit.error, gr=fit.error.grr, ui=ui,ci=ci) >> > Error in constrOptim(c(0.5, 0.3, 0.5), f = fit.error, gr = fit.error.grr, : > initial value not feasible > "Not feasible" means it doesn't satisfy the constraints. >> constrOptim(c(0.5,0.9,0.5), f=fit.error, gr=fit.error.grr, ui=ui,ci=ci) >> > Error in constrOptim(c(0.5, 0.9, 0.5), f = fit.error, gr = fit.error.grr, : > initial value not feasible > >> constrOptim(c(0.3,0.5,0.5), f=fit.error, gr=fit.error.grr, ui=ui,ci=ci) >> > Error in f(theta, ...) : argument "lambda1" is missing, with no default >
This time your starting values satisfied the constraints, so your objective function was called, but you didn't pass it a value for lambda1. > I only changed the parameters, how come the lambda1 that is not > missing in the first 2 cases suddently become missing? > > For your convenience, I put the complete code below: > > Best Wishes > Yuchen Luo > > ######################################## > rm(list = ls()) > > mat=5 > > rint=c(4.33,4.22,4.27,4.43,4.43,4.44,4.45,4.65,4.77,4.77) > tot=rep(13319.17,10) > sh=rep(1553656,10) > sigmae=c(0.172239074,0.188209271,0.193703774,0.172659891,0.164427247,0.24602361,0.173555309,0.186701165,0.193150456, > 0.1857315601) > ss=c(56.49,56.39,56.55,57.49,57.37,55.02,56.02,54.35,54.09, 54.67) > orange=rep(21.25,10) > > apple2=expression(rint*(1.0-rec)*(1.0-(pnorm(-lambda/2.0+log(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda)))/lambda)-((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda))*pnorm(-lambda/2.0-log(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda)))/lambda))+(exp(rint*(lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))))*((((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda))^(sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))+0.5)*pnorm(-log(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda)))/((sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt(mat+(lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))))-sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))*(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt(mat+(lambda*lambda/(sigmae*ss/(ss+lbar*(tot/s! h*! > > 1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))))+((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda))^(-sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))+0.5)*pnorm(-log(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda)))/((sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt(mat+(lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))))+sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))*(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt(mat+(lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))))))-(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda))^(sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))+0.5)*pnorm(-log(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda)))/((sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt((lambda*l! am! > bda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh* > 1000.0))))))-sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))*(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt((lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))))+((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda))^(-sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))+0.5)*pnorm(-log(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda)))/((sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt((lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))))+sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))*(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt((lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))))))))/((pnorm(-lambda/2.0+log(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda)))/lambda)-((ss+(tot/sh*1! 00! > > 0.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda))*pnorm(-lambda/2.0-log(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda)))/lambda))-(pnorm(-sqrt((sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*mat+lambda*lambda)/2.0+log(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda)))/sqrt((sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*mat+lambda*lambda))-((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda))*pnorm(-sqrt((sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*mat+lambda*lambda)/2.0-log(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda)))/sqrt((sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*mat+lambda*lambda)))*exp(-rint*mat)-(exp(rint*(lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))))*((((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda))^(sqrt(! 0.! > 25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar* > (tot/sh*1000.0))))+0.5)*pnorm(-log(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda)))/((sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt(mat+(lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))))-sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))*(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt(mat+(lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))))+((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda))^(-sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))+0.5)*pnorm(-log(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda)))/((sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt(mat+(lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))))+sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))*(sigmae*ss/(ss+! lb! > > ar*(tot/sh*1000.0)))*sqrt(mat+(lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))))))-(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda))^(sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))+0.5)*pnorm(-log(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda)))/((sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt((lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))))-sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))*(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt((lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))))+((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambda*lambda))^(-sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))+0.5)*pnorm(-log(((ss+(tot/sh*1000.0)*lbar)/(tot/sh*1000.0)/lbar*exp(lambd! a*! > lambda)))/((sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt((lambda*lambda/( > sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))))+sqrt(0.25+2.0*rint/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))*(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))*sqrt((lambda*lambda/(sigmae*ss/(ss+lbar*(tot/sh*1000.0)))/(sigmae*ss/(ss+lbar*(tot/sh*1000.0))))))))))) > > apple.ana= function(rec1,lambda1,lbar1) > {rec=rec1 > lambda=lambda1 > lbar=lbar1 > apple=eval(apple2) > gradient=cbind(eval(D(apple2,'rec')),eval(D(apple2,'lambda')), > eval(D(apple2,'lbar'))) > attr(apple.ana,'gradient')=gradient > apple > } > > fit.error=function(rec1,lambda1,lbar1) > {rec=rec1 > lambda=lambda1 > lbar=lbar1 > sum((eval(apple2)*1000-orange)^2/(orange^2)) > } > This is still coded incorrectly. Objective functions optimize over the first parameter only. See ?optim for the details. constrOptim is just a wrapper for optim. Duncan Murdoch > fit.error.grr=function(rec1,lambda1,lbar1) > {rec=rec1 > lambda=lambda1 > lbar=lbar1 > > drec=sum(20000*eval(D(apple2,'rec'))*(eval(apple2)*10000-orange)/(orange^2)) > dlambda=sum(20000*eval(D(apple2,'lambda'))*(eval(apple2)*10000-orange)/(orange^2)) > dlbar=sum(20000*eval(D(apple2,'lbar'))*(eval(apple2)*10000-orange)/(orange^2)) > > c(drec,dlambda,dlbar) > } > > ui=matrix(c(1,-1,0,0,0,0,0,0,1,-1,0,0,0,0,0,0,1,-1),6,3) > ci=c(0,-0.5,0,-2,0,-0.6) > > constrOptim(c(0.5,0.3,0.5), f=fit.error, gr=fit.error.grr, ui=ui,ci=ci) > constrOptim(c(0.5,0.9,0.5), f=fit.error, gr=fit.error.grr, ui=ui,ci=ci) > constrOptim(c(0.3,0.5,0.5), f=fit.error, gr=fit.error.grr, ui=ui,ci=ci) > > ########################################################### > > ______________________________________________ > R-help@stat.math.ethz.ch 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. > ______________________________________________ R-help@stat.math.ethz.ch 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.