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From |
Nick Cox <n.j.cox@durham.ac.uk> |

To |
"'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Looping and saving regression outputs |

Date |
Thu, 17 May 2012 19:08:18 +0100 |

Sorry, but that makes no sense to me. An observation in Stata is one row, case or record in your data. You can't fit a regression to one observation, any more than you can go . sysuse auto, clear (1978 Automobile Data) . regress mpg weight in 1 insufficient observations r(2001); I imagine you mean something else, but you have to tell us what it is. Nick n.j.cox@durham.ac.uk -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Sebastian Galarza 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. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Looping and saving regression outputs***From:*Fernando Rios Avila <f.rios.a@gmail.com>

**References**:**st: Looping and saving regression outputs***From:*Sebastian Galarza <sebastian@theicct.org>

**Fwd: st: Looping and saving regression outputs***From:*Ada Ma <heu034@gmail.com>

**Re: st: Looping and saving regression outputs***From:*Sebastian Galarza <sebastian@theicct.org>

**RE: st: Looping and saving regression outputs***From:*Nick Cox <n.j.cox@durham.ac.uk>

**Re: st: Looping and saving regression outputs***From:*Sebastian Galarza <sebastian@theicct.org>

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