You are not currently logged in.
Access JSTOR through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Local Likelihood Density Estimation Based on Smooth Truncation
Vol. 93, No. 2 (Jun., 2006), pp. 472-480
Stable URL: http://www.jstor.org/stable/20441297
Page Count: 9
You can always find the topics here!Topics: Estimators, Density estimation, Parametric models, Polynomials, Truncation, Statism, Objective functions, Wands, Censorship, Data smoothing
Were these topics helpful?See somethings inaccurate? Let us know!
Select the topics that are inaccurate.
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
Two existing density estimators based on local likelihood have properties that are comparable to those of local likelihood regression but they are much less used than their counterparts in regression. We consider truncation as a natural way of localising parametric density estimation. Based on this idea, a third local likelihood density estimator is introduced. Our main result establishes that the three estimators coincide when a free multiplicative constant is used as an extra local parameter.
Biometrika © 2006 Biometrika Trust