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Title: Local polynomial smoothing based on the Kaplan–Meier estimate
Authors: Bagkavos, Dimitrios
Ioannides, Dimitrios
Type: Article
Subjects: FRASCATI::Natural sciences::Mathematics
Keywords: Kaplan–Meier
Local polynomial fitting
Bandwidth selection
Issue Date: Dec-2022
Source: Journal of Statistical Planning and Inference
Volume: 221
First Page: 212
Last Page: 229
Abstract: The local polynomial modeling of the Kaplan–Meier estimate for random designs under the right censored data setting is investigated in detail. Two classes of boundary aware estimates are developed: estimates of the distribution function and its derivatives of any arbitrary order and estimates of integrated distribution function derivative products. Their statistical properties are quantified analytically and their implementation is facilitated by the development of corresponding data driven plug-in bandwidth selectors. The asymptotic rate of convergence of the plug-in rule for the estimates of the distribution function and its derivatives is quantified analytically. Numerical evidence is also provided on its finite sample performance. A real life data analysis illustrates how the methodological advances proposed herein help to generate additional insights in comparison to existing methods.
ISSN: 0378-3758
Other Identifiers: 10.1016/j.jspi.2022.04.006
Appears in Collections:Department of Economics

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