mathematical optimization - R DEoptim() function: How to select parameters to be opimised? -

i wish estimate parameters following example:

but how can make deoptim optimise 2 of 3 parameters? - there direct method this?

rm(list=ls()) t <- seq(0.1,20,length=100)  hobs <- 20 + 8*exp(-0.05*t) hsim <- function(p,t) {p[1] + p[2]*exp(-p[3]*t)} upper <- c(30,10,1) lower <- -upper  resfun <- function(p, t, hobs) {           r <- hobs - hsim(p,t)           return(t(r)%*%r) }  deoptim(resfun, lower, upper, hobs = hobs, t = t,                        deoptim.control(np = 80, itermax = 200, f = 1.2, cr = 0.7, trace =false)) 

i found workaround cf below. there more elegant way of doing this?

rm(list=ls()) t <- seq(0.1,20,length=100)  hobs <- 20 + 8*exp(-0.05*t) #hkorr <- rnorm(100,0,0.2) hsim <- function(p,t) {p[1] + p[2]*exp(-p[3]*t)} upper <- c(20,10,1) lower <- c(1,1,0.001) sel = c(0,1,1) ini = c(20,na,na) # correct upper , lower selected parameters upper <- upper[which(sel==1)] lower <- lower[which(sel==1)]  resfun <- function(par,t,hobs, sel, ini) {           p <- rep(na,3)           p[which(sel == 0)] <- ini[which(sel==0)]           p[which(sel == 1)] <- par           r <- hobs - hsim(p,t)           return(t(r)%*%r) } deoptim(resfun, lower, upper, hobs = hobs, t = t, sel = sel, ini = ini,         deoptim.control(np = 80, itermax = 200, f = 1.2, cr = 0.7, trace =false)) 

you can set upper , lower parameter value equal whichever parameter want hold constant.

# hold first parameter constant @ 20 opt <- deoptim(resfun, c(20, -10, -1), c(20, 10 ,1), hobs=hobs, t=t,                deoptim.control(np=80, itermax=200, f=1.2, cr=0.7))