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Re: st: multivariate lpoly
From
Jorge Eduardo Pérez Pérez <[email protected]>
To
"[email protected]" <[email protected]>
Subject
Re: st: multivariate lpoly
Date
Mon, 10 Mar 2014 15:28:41 -0400
I meant, it may help ...
--------------------------------------------
Jorge Eduardo Pérez Pérez
Graduate Student
Department of Economics
Brown University
On Mon, Mar 10, 2014 at 3:27 PM, Jorge Eduardo Pérez Pérez
<[email protected]> wrote:
> The package -ivqte- (SJ10-3 st0203) contains a subroutine, -locreg-
> wich performs local multivariate linear regression. Not exactly what
> you want, but I may help.
>
> --------------------------------------------
> Jorge Eduardo Pérez Pérez
> Graduate Student
> Department of Economics
> Brown University
>
>
> On Mon, Mar 10, 2014 at 3:19 PM, Nick Cox <[email protected]> wrote:
>> They are indeed different, and not exactly what you are asking for.
>>
>> Good luck to anyone capable of coding something quickly with
>> -mm_kern()- (as I think you mean).
>>
>> Note: please explain where user-written software you refer to comes
>> from (in this case -moremata- from SSC?).
>>
>>
>> Nick
>> [email protected]
>>
>>
>> On 10 March 2014 19:08, László Sándor <[email protected]> wrote:
>>> Thanks, Nick, Greg â I did look into -mfp- and -margintegrate- and
>>> both seem to do something different.
>>>
>>> I wonder if I should simply code up something quicky with -mf_mm_kern()-.
>>>
>>> Laszlo
>>>
>>> On Mon, Mar 10, 2014 at 2:19 PM, Nick Cox <[email protected]> wrote:
>>>> I'd restrict the descriptor "multivariate (anything) regression" to
>>>> multiple responses.
>>>>
>>>> Here you want multiple predictors: the official Stata offering
>>>> includes -mfp- and in addition there is a sibling spline family in
>>>> -mvrs- (SJ).
>>>>
>>>> One difficulty with a local polynomial is quite how you report it,
>>>> except as a series of graphs and an estimated response for every
>>>> distinct observation.
>>>>
>>>> Nick
>>>> [email protected]
>>>>
>>>>
>>>> On 10 March 2014 17:46, László Sándor <[email protected]> wrote:
>>>>> Hi all,
>>>>> I found some prior notes on the list about multivariate nonparametric
>>>>> regression, but no definitive conclusion. Is there something you would
>>>>> recommend now? Anything that scales as gracefully with the number of
>>>>> x's as possible? (The curse of dimensionality is always an issue with
>>>>> this kind of work.)
>>>>>
>>>>> Think of
>>>>> lpoly y x1 [x2 ...], generate(ybar)
>>>>> instead of the simple
>>>>> lpoly y x, generate(ybar)
>>>>>
>>>>> Some older code is available as kernreg.ado of Chuck Manski detailed
>>>>> in http://faculty.wcas.northwestern.edu/~cfm754/bounds_stata.pdf
>>>>>
>>>>> Thanks!
>>>>>
>>>>> Laszlo
>>>>>
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