Dear Professor Murdoch.
Thank you for your help!
1. I believe c(0.5,0.3,0.5) satisfies the constrain because I did the
following experiment
ui=-1*ui
ci=-1*ci
constrOptim(c(0.5,0.3,0.5), f=fit.error, gr=fit.error.grr, ui=ui,ci=ci)

The same error message pops up. Any theta ( in this case, c(0.5,0.3,0.5))
cannot violate both ui%*%theta>=ci and -ui%*%theta>=-ci.

2. There is lambda1 available. The 0.3 in c(0.5,0.3,0.5) is lambda1. If you
plug c(0.5,0.3,0.5) into fit.error and fit.error.grr by
fit.error(0.5,0.3,0.5)
fit.error.grr(0.5,0.3,0.5)
It works.

Best Wishes
Yuchen Luo




On 9/10/07, Duncan Murdoch <murdoch@stats.uwo.ca> wrote:
>
> 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/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((lambda*lam!
> >  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*100!
> >  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(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)))))))))))
> >
> > 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.
> >
>
>
>

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