Firstly, I would like to thank Nick Cox, Roger Newson, Steven Olley and
Jeffrey Pitlabo for their commends and advices.
I have purchased the Stata Journal 2003, Vol.3, No.4, and I have just
finished reading the description of -locpoly-. I still have some questions:
(1)Since -locpoly- implements the Nadaraya(1964) and Watson(1964) estimator
estimator (the same as the -kernreg- command), shall I assume that a local
mean (constant) polynomial smooth (of order p=0) will be the same as
-kernreg-? (assumning the same bandwidth, kernel and gridpoints)
(2)If -width- is not specified in the -locpoly- options, then the default
is used which is described as 'optimal' by the authors of kdensity and
kernreg. However, the authors of -locpoly- described this default bandwidth
as "entirely inappropriate for local polynomial smoothing". It further
advices that I should start with the default and adjust it according to my
needs. However, I do not wish to choose a bandwidth that relies only on
visual criteria, since the badwidth essentialy defines the cosistency of
the estimation. How can I define (statistically) such an 'appropriate'
bandwidth for polynomial smoothing? Any advices? Any specific references?
(the libray of my university does not have Fan and Gijbels (1996) and is
about 48.00GBP to purchase the textbook)
(3)I understand that there is a great negative relation between the
specified number of points (grids) to be estimated and the computing
intensity. I have many datasets that vary from 100 to 30,000 observations.
Since is will take a lot of time to experiment with many combinations of
-n(#)- is there a 'rule of thumb' that defines the number of points to be
specfied as a function of the number of observations.
(4)Since I am mostly interested in revealing patterns in the middle of the
distribution (and not so much in the tails), is there a way to specify more
grid points in the middle? How can I generate such a variable so that I
included it in the option -at(var)-? What am I missing here?
many thanks in advance
Dimitris
Roger Newson wrote:
>
> At 12:33 01/06/04 +0100, Dimitris wrote:
> >(2) Has anyone written something on nonparametric smoothing for
> >higher-dimensions, i.e. more than one explanatory variables ?
>
> My own -frencurv- program (part of the -bspline- package downloadable from
> SSC) can be used for additive spline modelling with more than one
> explanatory variable. Jonathan Sterne and I are currently in the process of
> preparing a paper on the subject for submission to Statistics in Medicine.
>
> Best wishes
>
> Roger
>
> --
> Roger Newson
> Lecturer in Medical Statistics
> Department of Public Health Sciences
> King's College London
> 5th Floor, Capital House
> 42 Weston Street
> London SE1 3QD
> United Kingdom
>
> Tel: 020 7848 6648 International +44 20 7848 6648
> Fax: 020 7848 6620 International +44 20 7848 6620
> or 020 7848 6605 International +44 20 7848 6605
> Email: [email protected]
> Website: http://www.kcl-phs.org.uk/rogernewson
>
> Opinions expressed are those of the author, not the institution.
>
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--
---------------------------------------------
Dimitris Christodoulou
School for Business and Regional Development
University of Wales, Bangor
Hen Coleg
LL57 2DG Bangor
UK
e-mail: [email protected]
---------------------------------------------
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