turn on suggestions

Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.

Showing results for

Find a Community

Topic Options

- RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

02-19-2016 04:29 AM

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

Accepted Solutions

Solution

02-19-2016
01:09 PM

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Posted in reply to dannegrila

02-19-2016 09:14 AM

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.

All Replies

Solution

02-19-2016
01:09 PM

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Posted in reply to dannegrila

02-19-2016 09:14 AM

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.

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Posted in reply to Rick_SAS

02-19-2016 09:32 AM

Many thanks Rick.

P.S. exp(.) stands for matrix exponential (expmatrix)