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Re: st: RE: new package margdistfit available on SSC
From
Maarten Buis <[email protected]>
To
[email protected]
Subject
Re: st: RE: new package margdistfit available on SSC
Date
Sat, 19 Nov 2011 09:45:24 +0100
I'll see what I can do. A quick fix is that you can compile the mata
code yourself by running the .do file margdistfit_mata.do, which is
available in the ancillirry files.
-- Maarten
On Sat, Nov 19, 2011 at 4:18 AM, David Ashcraft
<[email protected]> wrote:
> I can not run -margdisfit- on Stata - 11, Please see below.
>
> margdistfit, qq
> (marg_norminvert() in lmargdistfit, compiled by Stata 12.0, is too new to be run by this version of Stata and so was ignored)
> <istmt>: 3499 marg_norminvert() not found
> r(3499);
>
>
>
> ----- Original Message -----
> From: "Feiveson, Alan H. (JSC-SK311)" <[email protected]>
> To: "[email protected]" <[email protected]>
> Cc:
> Sent: Friday, November 18, 2011 4:53:35 PM
> Subject: st: RE: new package margdistfit available on SSC
>
> Maarten - Thank you! I have been doing this "by hand" for years!
>
> Al
>
> -----Original Message-----
> From: [email protected] [mailto:[email protected]] On Behalf Of Maarten Buis
> Sent: Friday, November 18, 2011 3:48 AM
> To: [email protected]
> Subject: st: new package margdistfit available on SSC
>
> Thanks to Kit Baum a package, -margdistfit-, is now available from
> SSC. -margdistfit- displays graphs that can help determine how well a
> distributional assumption made in a parametric regression model fits
> to the data. It does so by comparing the distribution of the dependent
> variable with the marginal distribution implied by the model. To
> install -margdistfit- type in Stata: -ssc install margdistfit-.
>
> In parametric regression models a distribution is assumed for the
> dependent variable, but its parameters, typically the mean, is
> allowed to change from observation to observation depending on the
> values of the explantory variables. So the distribution of the
> dependent variable implied by the model is a mixture of N
> distributions, such that each component distribution has the
> parameters of one of the observations. This is the called the marginal
> distribution. If the distributional assumption is correct than this
> marginal distribution should correspond with the distribution of the
> dependent variable. -margdistfit- compares the two distribution with a
> probabiltiy-probability plot (to investigate the middle of the
> distribution) and a quantile-quantile plot (to investigate the tails).
> It can also show the two cumulative density functions. Examples can
> be found at <http://www.maartenbuis.nl/software/margdistfit.html>.
>
> The current version of -margdistfit- can be used after -regress- and
> -betafit-, the latter is available from SSC.
>
> I hope some of you will find it useful,
> Maarten
>
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
>
> http://www.maartenbuis.nl
> --------------------------
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>
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>
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>
--
--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://www.maartenbuis.nl
--------------------------
*
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