Nothing
#Example: Wood function
#
wood.f <- function(x){
res <- 100*(x[1]^2-x[2])^2+(1-x[1])^2+90*(x[3]^2-x[4])^2+(1-x[3])^2+
10.1*((1-x[2])^2+(1-x[4])^2)+19.8*(1-x[2])*(1-x[4])
attr(res,"fname")<-"WoodHess"
return(res)
}
#gradient:
wood.g <- function(x){
g1 <- 400*x[1]^3-400*x[1]*x[2]+2*x[1]-2
g2 <- -200*x[1]^2+220.2*x[2]+19.8*x[4]-40
g3 <- 360*x[3]^3-360*x[3]*x[4]+2*x[3]-2
g4 <- -180*x[3]^2+200.2*x[4]+19.8*x[2]-40
return(c(g1,g2,g3,g4))
}
#hessian:
wood.h <- function(x){
h11 <- 1200*x[1]^2-400*x[2]+2; h12 <- -400*x[1]; h13 <- h14 <- 0
h22 <- 220.2; h23 <- 0; h24 <- 19.8
h33 <- 1080*x[3]^2-360*x[4]+2; h34 <- -360*x[3]
h44 <- 200.2
H <- matrix(c(h11,h12,h13,h14,h12,h22,h23,h24,
h13,h23,h33,h34,h14,h24,h34,h44),ncol=4)
return(H)
}
wood.fgh <- function(x){
fval <- wood.f(x)
gval <- wood.g(x)
hval <- wood.h(x)
attr(fval,"gradient") <- gval
attr(fval,"hessian")<- hval
fval
}
#################################################
x0 <- c(-3,-1,-3,-1) # Wood standard start
# direct call to nlm
t1nlm <- nlm(wood.fgh, x0, print.level=0)
print(t1nlm)
# But optimr with nlm uses a larger iteration limit, and gets to a possible solution
t1nlmo <- optimr(x0, wood.f, wood.g, hess=wood.h, method="nlm", control=list(maxit=100))
proptimr(t1nlmo)
print(wood.g(t1nlmo$par))
tst<-try(t1nlminbo <- optimr(x0, wood.f, wood.g, hess=wood.h, method="nlminb"))
if (class(tst) == "try-error"){
cat("try-error on attempt to run nlminb in optimr()\n")
} else { proptimr(t1nlminbo) }
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