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# GenRoseHess.R
# genrosa function code -- attempts to match the rosenbrock at gs=100 and x=c(-1.2,1)
genrosa.f<- function(x, gs=NULL){ # objective function
## One generalization of the Rosenbrock banana valley function (n parameters)
n <- length(x)
if(is.null(gs)) { gs=100.0 }
# Note do not at 1.0 so min at 0
fval<-sum (gs*(x[1:(n-1)]^2 - x[2:n])^2 + (x[1:(n-1)] - 1)^2)
}
attr(genrosa.f, "fname")<-"genrosa"
genrosa.g <- function(x, gs=NULL){
# vectorized gradient for genrose.f
# Ravi Varadhan 2009-04-03
n <- length(x)
if(is.null(gs)) { gs=100.0 }
gg <- as.vector(rep(0, n))
tn <- 2:n
tn1 <- tn - 1
z1 <- x[tn] - x[tn1]^2
z2 <- 1 - x[tn1]
# f = gs*z1*z1 + z2*z2
gg[tn] <- 2 * (gs * z1)
gg[tn1] <- gg[tn1] - 4 * gs * x[tn1] * z1 - 2 *z2
return(gg)
}
genrosa.h <- function(x, gs=NULL) { ## compute Hessian
if(is.null(gs)) { gs=100.0 }
n <- length(x)
hh<-matrix(rep(0, n*n),n,n)
for (i in 2:n) {
z1<-x[i]-x[i-1]*x[i-1]
# z2<-1.0 - x[i-1]
hh[i,i]<-hh[i,i]+2.0*(gs+1.0)
hh[i-1,i-1]<-hh[i-1,i-1]-4.0*gs*z1-4.0*gs*x[i-1]*(-2.0*x[i-1])
hh[i,i-1]<-hh[i,i-1]-4.0*gs*x[i-1]
hh[i-1,i]<-hh[i-1,i]-4.0*gs*x[i-1]
}
return(hh)
}
require(optimx)
cat("Generalized Rosenbrock tests\n")
cat("original n and x0")
x0 <- c(-1.2, 1)
# solorigs <- snewton(x0, genrosa.f, genrosa.g, genrosa.h) # WORKS OK if optimx loaded
solorig <- optimr(x0, genrosa.f, genrosa.g, genrosa.h, method="snewton", hessian=TRUE)
proptimr(solorig)
print(eigen(solorig$hessian)$values)
solorigm <- optimr(x0, genrosa.f, genrosa.g, genrosa.h, method="snewtonm", hessian=TRUE)
proptimr(solorigm)
print(eigen(solorigm$hessian)$values)
# Start with 50 values of pi and scale factor 10
x0 <- rep(pi, 50)
sol50pi <- optimr(x0, genrosa.f, genrosa.g, genrosa.h, method="snewton",
hessian=TRUE, gs=10)
proptimr(sol50pi)
print(eigen(sol50pi$hessian)$values)
hhi <- genrosa.h(sol50pi$par, gs=10)
print(eigen(hhi)$values)
sol50pim <- optimr(x0, genrosa.f, genrosa.g, genrosa.h, method="snewtonm",
hessian=TRUE, gs=10)
proptimr(sol50pim)
hhm <- genrosa.h(sol50pim$par, gs=10)
print(eigen(hhm)$values)
# Bounds constraints
lo<-rep(3,50)
up<-rep(4,50)
sol50pimb <- optimr(x0, genrosa.f, genrosa.g, genrosa.h, lower=lo, upper=up, method="snewtonm",
hessian=TRUE, gs=10)
proptimr(sol50pimb)
# approximate hessian
solom01 <- optimr(x0, genrosa.f, gr=NULL, hess="approx", method="snewtonm", hessian=TRUE)
proptimr(solom01)
print(eigen(solom01$hessian)$values)
solomg1 <- optimr(x0, genrosa.f, genrosa.g, hess="approx", method="snewtonm", hessian=TRUE)
proptimr(solomg1)
print(eigen(solomg1$hessian)$values)
# Following should fail
solomrr <- try(optimr(x0, genrosa.f, gr=NULL, hess="rubbish", method="snewtonm", hessian=TRUE))
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