NLSQBOX.OMS
Script File:
# Description:
# Solves nonlinear least squares with box constraint.
#
clear
# nonlinear function
function f(x) begin
return {exp(x(1)) - exp(1.), exp(x(2)) - exp(2.)}
end
#
# level of tracing inside of nlsqbox
level = 0
# maximum number of iterations
maxit = 20
# initial x value
xini = {0., 0.}
# lower limit for x
xlow = { - 1., - 1.}
# upper limit for x
xup = { + 1., + 1.}
# store all the iterates
x = nlsqbox(function f, xini, xlow, xup, maxit, level)
# number of iterations
nitr = coldim(x) - 1
# minimizer subject to constraints
argmin = x.col(nitr + 1)
#
print "minimizing the sum of the squares of the components of"
print "{exp(x(1)) - exp(1.), exp(x(2) - exp(2.)}"
print "subject to", xlow(1), "<=", "x(1)", "<=", xup(1)
print " ", xlow(2), "<=", "x(2)", "<=", xup(2)
print "xini' =", xini'
print "argmin' =", argmin'
print "nitr =", nitr
Output:
minimizing the sum of the squares of the components of
{exp(x(1)) - exp(1.), exp(x(2) - exp(2.)}
subject to -1 <= x(1) <= 1
-1 <= x(2) <= 1
xini' = [ 0 , 0 ]
argmin' = [ 1 , 1 ]
nitr = 2
