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Thread Subject:
regressor selection techniques

Subject: regressor selection techniques

From: Mel

Date: 28 Oct, 2009 20:11:04

Message: 1 of 3

I am new to Matlab, transitioning from SAS and hoping for some hope. In SAS there is a selection technique used in regression to limit the number of regressors to the best ‘n’ of a data set. For example: select the best 6 of 20 repressors’ to explain Y based upon the adjusted rsquare. Is there a similar technique in Matlab?

Thanks,
Mel

Subject: regressor selection techniques

From: Richard Willey

Date: 29 Oct, 2009 12:23:24

Message: 2 of 3


"Mel " <melkunkel@u.boisestate.edu> wrote in message
news:hca8go$n9p$1@fred.mathworks.com...
>I am new to Matlab, transitioning from SAS and hoping for some hope. In SAS
>there is a selection technique used in regression to limit the number of
>regressors to the best ‘n’ of a data set. For example: select
>the best 6 of 20 repressors’ to explain Y based upon the adjusted
>rsquare. Is there a similar technique in Matlab?
>
> Thanks,
> Mel

Hi Mel

The Statistics Toolbox has a lot of functionality to help you solve this
type of problem.

You can review all of the Statistics Toolbox documentation on the web. I'd
recommend that you start with the following section

http://www.mathworks.com/access/helpdesk/help/toolbox/stats/index.html?/access/helpdesk/help/toolbox/stats/brj0qbu.html&http://www.google.com/search?sourceid=navclient&ie=UTF-8&rlz=1T4GPTB_enUS290US290&q=MATLAB+sequentialfs

We also provide some nice demos that you can use to familiarize yourself
with the features and functions

The demo titled "Partial Least Squares Regression and Principal Components
Regression" is probably the best place to start.

http://www.mathworks.com/products/statistics/demos.html?file=/products/demos/shipping/stats/plspcrdemo.html

The demo includes feature selection techniques as well as feature
transformation.

regards,

Richard

Subject: regressor selection techniques

From: Mel

Date: 29 Oct, 2009 17:09:19

Message: 3 of 3


Thanks Richard

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