-l2cvwarp- gives one of several competing choices for "optimum"
bandwidth in kernel density estimation, a univariate problem. I don't
see what that has to do with lowess- (a bivariate problem in Stata) or
-plreg- (a trivariate or higher problem).
There's a small industry in such criteria that tests and exhibits the
competence of mathematical statisticians. For practical data analysis a
better test is consistency with scientific or practical needs as given
by the context of your problem.
Nick
[email protected]
Lazarte Alcala, Naneida
I have used the command l2cvwarp (not part of official Stata, it is in
STB 27/snp6_2) which is the WARPing version of the L2CV (Least squares
cross-validation method) to determine the optimal bandwidth that I need
to use for performing nonparametric estimation. From the command I
obtain the bandwidth that minimizes the L2CV function, which is 4,000,
but now I need to "translate it" in order to use it in the plreg
command (this one is also a user-written command that performs
semiparametric estimation). The plreg command option bandw() accepts
bandwidths between 0 and 1, e.g. a bandwidth 0.8, which is de default
one, says that 80% of the data is being used to the smoothing at each x.
Can anybody tell me how I should understand the bandwidth from l2cvwarp
and put it in terms of the plreg command?(this command uses lowess to
estimate the nonparametric part of the model).
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