Re: st: Looping and saving regression outputs

[Sebastian Galarza <sebastian@theicct.org>]

Thanks (Nick, Fernando and Ada Ma) this looks like its working. By the way, sizef is size of field (working on oil data). 



On May 17, 2012, at 11:34 AM, Fernando Rios Avila wrote:

> oops
> You are totally right. The code should be like this:
>> foreach i in 1 2 3 4 5 6 7 8 9 10 {
>> reg y x if sizef==`i'
>> matrix betas=nullmat(beta) \ e(b)
>> matrix r2=nullmat(r2), e(r2)
>> matrix s2=nullmat(s2), e(V)
>> }
> 
> And the Size of firm...I guess too much work on my own data.
> Fernando
> On Thu, May 17, 2012 at 2:27 PM, Nick Cox <n.j.cox@durham.ac.uk> wrote:
>> This sounds more likely to be what Sebastian wants, but note that this loop repeats exactly the same code each time round the loop. Something like an -if- condition is presumably needed inside.
>> 
>> (How you do know that -sizef- is "size of firm"? Immaterial, but it's nowhere stated.)
>> 
>> Nick
>> n.j.cox@durham.ac.uk
>> 
>> 
>> -----Original Message-----
>> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Fernando Rios Avila
>> Sent: 17 May 2012 19:20
>> To: statalist@hsphsun2.harvard.edu
>> Subject: Re: st: Looping and saving regression outputs
>> 
>> Ok Sebastian,
>> So i believe what you want do is use different samples identified by
>> the size of the firm which is given in the variable sizef.
>> My answer, then, is more "manual". The first thing you need to have is
>> a list of all the possible groups you can obtain by sizef. A simple -
>> tab sizef -, or a recode of sizef should work here.
>> Lets say now that you have 10 groups. Your loop then should look something like:
>> 
>> foreach i in 1 2 3 4 5 6 7 8 9 10 {
>> reg y x
>> matrix betas=nullmat(beta) \ e(b)
>> matrix r2=nullmat(r2), e(r2)
>> matrix s2=nullmat(s2), e(V)
>> }
>> 
>> that should save your betas, the R2 and the variance-covariance
>> matrix. You might need to modify it specifically for your purposes in
>> the case of the var_covar matrix, since you only want the standard
>> errors.
>> 
>> Hope this helps
>> F
>>> Sent: 17 May 2012 19:01
>>> To: statalist@hsphsun2.harvard.edu
>>> Subject: Re: st: Looping and saving regression outputs
>>> 
>>> Nick et al,
>>> 
>>> Sorry for the lack of clarity. I will try to be more clear now and in future posts.
>>> 
>>> Here goes:
>>> 
>>> I have a panel dataset with several variables, including (sizef) with around 50,000 observations.
>>> The code that I am running does not contain the cycling/loop because I am unsure how to write it.
>>> 
>>> So the first question/problem is that:
>>> I would like to cycle through each observation of sizef and run each of three regressions.
>>> 
>>> The second question/problem regards:
>>> Recovering the coefficient vector, r2 and standard errors in a matrix.
>>> 
>>> After recovering these values for each observation, I want to create a histogram by regression for each of these values (coefficients, r2 and standard errors) to get a visual representation of how they are distributed.
>>> 
>>> I hope this helps clarify my issue.
>>> 
>>> On May 17, 2012, at 10:37 AM, Nick Cox wrote:
>>> 
>>>> I think it's the other way round. What you are doing precisely is unclear and more detailed advice is difficult for that reason.
>>>> 
>>>> For example:
>>>> 
>>>> You refer to cycling over variables -sizef- but it is not clear where -sizef- appears in your code.
>>>> 
>>>> You say you have 51,000 variables, but no Stata allows more than 32,767 variables. Do you mean observations?
>>>> 
>>>> Ada's very helpful reply is about as detailed as you can expect until you clarify such details.
>>>> 
>>>> For "STATA" read "Stata".
>>>> 
>>>> Nick
>>>> n.j.cox@durham.ac.uk
>>>> 
>>>> Sebastian Galarza
>>>> 
>>>> Ada Ma et al,
>>>> 
>>>> Thank you for your response. Can you be a little bit more explicit in the coding of this? I am still far from being a STATA power user and some examples might be helpful. Im looking into the svmat command and its a good starting point. Thanks for your input,
>>>> 
>>>> On May 17, 2012, at 8:15 AM, Ada Ma wrote:
>>>> 
>>>>> First you can create one matrix for each regression by stacking the r2
>>>>> on to the coefficients.  So say you have Q explanatory variable your
>>>>> row matrix would be 1 x (Q+1+1) (one for the constant one for the r2).
>>>>> You might also consider adding the SEs to your matrix too.  You might
>>>>> want to add an extra item at the top end of your matrix to label your
>>>>> regressions too to save your effort.
>>>>> 
>>>>> Then you can stack all the regression results into one big matrix.
>>>>> 
>>>>> Then after you have done all the loopings use -svmat- to turn your big
>>>>> matrix into variables.
>>>>> 
>>>>> Then finally you -outsheet- those variables into a CSV or save the new
>>>>> variables as a separate Stata dataset.
>>>> 
>>>> 
>>>> On Wed, May 16, 2012 at 6:22 PM, Sebastian Galarza
>>>> 
>>>>>> I want to run the following code and save the beta values and r2 for three different regressions in a matrix such as this:
>>>>>> 
>>>>>> Variable B0a B1a B2a R2a B1b B2b B3b R2b B1c B2c B3c R2c
>>>>>> 1
>>>>>> 2
>>>>>> 3
>>>>>> 
>>>>>> I have a total of 51000 variables (sizef) so that the code I would like to run is:
>>>>>> 
>>>>>> 
>>>>>> *for each variable sizef
>>>>>> 
>>>>>> nl (P_WOR = {b0=0.1}*(1 * exp({b1=0.05}* (ageyear))))
>>>>>> predict a
>>>>>> matrix list e(b)
>>>>>> display e(r2)
>>>>>> 
>>>>>> * save beta values and r2
>>>>>> 
>>>>>> nl log3: P_WOR ageyear
>>>>>> predict b
>>>>>> matrix list e(b)
>>>>>> display e(r2)
>>>>>> 
>>>>>> * save beta values and r2
>>>>>> 
>>>>>> nl gom3: P_WOR ageyear
>>>>>> predict c
>>>>>> matrix list e(b)
>>>>>> display e(r2)
>>>>>> 
>>>>>> * save beta values and r2
>>>>>> 
>>>>>> Any help would be greatly appreciated.
>> 
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