Hi,
How can I solve in IML a minimization problem as following?
Having a known matrix e.g. M= {0.8 0.2, 0.4 0.6} and a known generator matrix G, I want to solve a and b (a diagonal matrix A) such that the distance between M[,2] and exp(A*G) [,2] is minimized – basically the minimization is addressed to the last column in matrices only ...
Many thanks,
Dan
Your objective function is
SSQ( (exp(A*G) - M)[,2] )
Write the function to be minimized as a function of the diagonal parameters a and b. You can use any NLP routine to minimize the function.
There are many examples on my blog (search for 'NLPNRA') . Start with the article that maximizes the likelihood function, which includes links to the NLP documentation. Set opt[1]=0 to specify minimization.
Your objective function is
SSQ( (exp(A*G) - M)[,2] )
Write the function to be minimized as a function of the diagonal parameters a and b. You can use any NLP routine to minimize the function.
There are many examples on my blog (search for 'NLPNRA') . Start with the article that maximizes the likelihood function, which includes links to the NLP documentation. Set opt[1]=0 to specify minimization.
Many thanks Rick.
P.S. exp(.) stands for matrix exponential (expmatrix)
Join us for SAS Innovate 2025, our biggest and most exciting global event of the year, in Orlando, FL, from May 6-9. Sign up by March 14 for just $795.
Learn how to run multiple linear regression models with and without interactions, presented by SAS user Alex Chaplin.
Find more tutorials on the SAS Users YouTube channel.