The following may or may not be relevant, but definitely getting somewhat
different results.
As this was a quick and dirty try while having a snack, it may have bugs.
# Lobo2412.R -- from R Help 20241213
#Original artificial data
library(optimx)
library(nloptr)
library(alabama)
set.seed(1)
A <- 1.34
B <- 0.5673
C <- 6.356
D <- -1.234
x <- seq(0.5, 20, length.out = 500)
y <- A + B * x + C * x^2 + D * log(x) + runif(500, 0, 3)
#Objective function
X <- cbind(1, x, x^2, log(x))
flobo <- function(theta) {
sum(abs(X %*% theta - y))
}
#Constraint
eps <- 1e-4
hinlobo <- function(theta) {
abs(sum(X %*% theta) - sum(y)) - 1e-3 + eps # ?? weird! (1e-4 - 1e-3)
}
Hxlobo <- function(theta) {
X[100, , drop = FALSE] %*% theta - (120 - eps) # ditto -- also constant
}
conobj<-function(tt){
ob <- flobo(tt)
ci <- hinlobo(tt)
if (ci > 0) {ci <- 0}
ce <- Hxlobo(tt)
si<-1; se<-1
val<-ob+si*ci^2+se*ce^2
cat("f, ci, ce,ob,val:"," ",ci," ",ce," ",ob," ",val," at "); print(tt)
val
}
t0<-rep(0,4)
conobj(t0)
t1 <- c(2.02, 6.764, 6.186, -20.095)
conobj(t1)
t2 <- c( -0.2186159, -0.5032066, 6.4458823, -0.4125948)
conobj(t2)
solo<-optimr(t0, conobj, gr="grcentral", method="anms", control=list(trace=1))
solo
conobj(solo$par)
#Optimization with nloptr
# Sol = nloptr::auglag(t0, flobo, eval_g_ineq = hinlobo, eval_g_eq = Hxlobo,
opts =
# list("algorithm" = "NLOPT_LN_COBYLA", "xtol_rel" = 1.0e-8, print_level=1))
# -0.2186159 -0.5032066 6.4458823 -0.4125948
sol <- auglag(par=t0, fn=flobo, hin=hinlobo, heq=Hxlobo,
control.outer=list(trace=TRUE))
sol
#==================================
J Nash
On 2024-12-13 13:45, Duncan Murdoch wrote:
You posted a version of this question on StackOverflow, and were given advice
there that you ignored.
nloptr() clearly indicates that it is quitting without reaching an optimum, but you are hiding that message. Don't do
that.
Duncan Murdoch
On 2024-12-13 12:52 p.m., Daniel Lobo wrote:
library(nloptr)
set.seed(1)
A <- 1.34
B <- 0.5673
C <- 6.356
D <- -1.234
x <- seq(0.5, 20, length.out = 500)
y <- A + B * x + C * x^2 + D * log(x) + runif(500, 0, 3)
#Objective function
X <- cbind(1, x, x^2, log(x))
f <- function(theta) {
sum(abs(X %*% theta - y))
}
#Constraint
eps <- 1e-4
hin <- function(theta) {
abs(sum(X %*% theta) - sum(y)) - 1e-3 + eps
}
Hx <- function(theta) {
X[100, , drop = FALSE] %*% theta - (120 - eps)
}
#Optimization with nloptr
Sol = nloptr(rep(0, 4), f, eval_g_ineq = hin, eval_g_eq = Hx, opts =
list("algorithm" = "NLOPT_LN_COBYLA", "xtol_rel" = 1.0e-8))$solution
# -0.2186159 -0.5032066 6.4458823 -0.4125948
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______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide https://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
