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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


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