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Re: st: RE: One question about LARS package


From   Kun Li <[email protected]>
To   [email protected]
Subject   Re: st: RE: One question about LARS package
Date   Tue, 22 Jan 2013 22:23:38 +0100

Dear Peter,

Thank you for your response. I think your suggestion would be a
feasible alternative. However, such restriction would be similar to
directly restricting the number of regressors at RHS, so it lacks the
flexibility to have a smaller value on the tuning parameters (as I may
still have different number of regressors for different data for small
tuning parameter, instead of a fixed number of regressors). A further
question would be, can I have a method to compare step 3, 4, and 5?
Does it make sense if I compute the norm for all the coefficients at
each step and compare with the parameter I set to select from these
three steps? Thank you very much for your help.

Best

Kun

2013/1/22 Lachenbruch, Peter <[email protected]>:
> can you just use the model at step 3? or step 4?  You'll need to rerun the regress command with those three variables.
>
> Peter A. Lachenbruch,
> Professor (retired)
> ________________________________________
> From: [email protected] [[email protected]] on behalf of Kun Li [[email protected]]
> Sent: Tuesday, January 22, 2013 12:25 AM
> To: [email protected]
> Subject: st: One question about LARS package
>
> Dear Stata Users
>
> I have one question using LARS package in stata. I have one particular
> application that tries to use lars for model selection. Basically I
> have one y and x1, x2, ....up to x12. The default lars command gives
> me the results as follows
>
> Cp, R-squared and Actions along the sequence of models
>
> +------------------------------------------+
> | Step | Cp | R-square | Action |
> |------+-------------+----------+----------|
> | 1 | 276.7940 | 0.0000 | |
> | 2 | 249.3110 | 0.0292 | +x6 |
> | 3 | 95.0027 | 0.1840 | +x5 |
> | 4 | 13.1299 | 0.2670 | +x7 |
> | 5 | 13.2321 | 0.2689 | +x8 |
> | 6 | 14.7937 | 0.2694 | +x9 |
> | 7 | 15.4561 | 0.2707 | +x11 |
> | 8 | 14.4944 | 0.2736 | +x4 |
> | 9 | 13.2267 | 0.2769 | +x3 |
> | 10 | 13.6023 | 0.2785 | +x1 |
> | 11 | 13.6600 | 0.2804 | +x2 |
> | 12 | 12.2079 *| 0.2838 | +x10 |
> | 13 | 13.0000 | 0.2850 | +x12 |
> +------------------------------------------+
>
> So this gives a model with 11 regressors on the RHS. However, this
> number (11) is still too big for the application. Ideally it would be
> around 3-5. And my question is:
>
> Is there a way for me to reduce the regressors on the RHS to be 3-5?
> Does this have anything to do with the tuning parameter? And if so,
> does LARS package allow user to adjust tuning parameters?
>
> Thanks for your help!
>
> Best
>
> Kun
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