Timeline for How do I build a regression model with integer constraints on parameters?
Current License: CC BY-SA 3.0
11 events
| when toggle format | what | by | license | comment | |
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| Apr 13, 2017 at 12:44 | history | edited | CommunityBot |
replaced http://stats.stackexchange.com/ with https://stats.stackexchange.com/
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| Jul 18, 2016 at 16:59 | comment | added | Mark L. Stone | I just came across this ready to go MATLAB package which explicitly deals with (mixed0 integer least squares problems cs.mcgill.ca/~chang/software/MILES.php . | |
| Jul 13, 2016 at 8:38 | vote | accept | dreamflasher | ||
| Jul 8, 2016 at 16:05 | comment | added | Mark L. Stone | As per @hxd1011 's answer, if the number of integer parameters to be estimated s sufficiently small, brute force evaluation of the sum square of residuals for all possible combinations of parameter values is another option. The methods I mentioned in the preceding comment can be many times faster than brute force evaluation, because they are able to intelligently prune out possibilities, as the algorithm proceeds, which must be inferior to already evaluated parameter value combinations. | |
| S Jul 8, 2016 at 16:04 | history | suggested | Haitao Du | CC BY-SA 3.0 |
make tile more informative for integer constraint.
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| Jul 8, 2016 at 16:01 | comment | added | Mark L. Stone | How many $\pi_i$ 's are there? Are the $\pi_i$'s the only parameters to be estimated, or are there also continuous parameters? This should be solvable by use of (mixed) integer quadratic programming, for which there are many off the shelf solvers, both free and commercial. The actual computational difficulty for the solver to find the optimal solution depends on the size and difficulty of the problem. Another option would be to solve this as a (mixed) integer Second Order Cone Problem (SOCP), which may or may not be easier (faster) to solve, but requires more knowledge to formulate. | |
| Jul 8, 2016 at 15:56 | comment | added | user78229 | Canned software packages and modules don't always offer such options. On the other hand, SEMs and/or nonlinear models typically offer the most flexibility in this regard. Of course, both assume that an explicit model of some type has been formulated. In other words, these are not exploratory, variable selection procedures. | |
| Jul 8, 2016 at 15:52 | review | Suggested edits | |||
| S Jul 8, 2016 at 16:04 | |||||
| Jul 8, 2016 at 15:42 | answer | added | Haitao Du | timeline score: 3 | |
| Jul 8, 2016 at 15:36 | review | First posts | |||
| Jul 8, 2016 at 15:37 | |||||
| Jul 8, 2016 at 15:35 | history | asked | dreamflasher | CC BY-SA 3.0 |