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The limit distribution of dynamic programming estimators of multiple change points
Author(s):
R.
E.
Maiboroda;
O.
V.
Sugakova
Translated by:
S. Kvasko
Original publication:
Teoriya Imovirnostei ta Matematichna Statistika,
vipusk 69
(2003).
Journal:
Theor. Probability and Math. Statist.
No. 69
(2004),
103-113.
MSC (2000):
Primary 62G20;
Secondary 93E10
Posted:
February 8, 2005
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Additional information
Abstract:
We consider a problem of estimating multiple change points in the case where the distributions of observations between change points belong to a finite family of known distributions. We describe a dynamic programming procedure of the estimation and a method for improving estimators that generalizes the averaged likelihood method. The limit distributions of these estimators are given in terms of the argument of the minimum of random walks. We show that these distributions, for an appropriate set of parameters, coincide with those of the maximum likelihood estimators or averaged likelihood estimator for models with only one change point.
References:
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Additional Information:
R.
E.
Maiboroda
Affiliation:
Faculty for Mechanics and Mathematics, Kyiv National Taras Shevchenko University, Volodymyrs'ka Street 63, Kyiv, Ukraine
Email:
mre@mechmat.univ.kiev.ua
O.
V.
Sugakova
Affiliation:
Faculty for Mechanics and Mathematics, Kyiv National Taras Shevchenko University, Volodymyrs'ka Street 63, Kyiv, Ukraine
Email:
sugak@univ.kiev.ua
DOI:
10.1090/S0094-9000-05-00618-6
PII:
S 0094-9000(05)00618-6
Received by editor(s):
27/JAN/2003
Posted:
February 8, 2005
Copyright of article:
Copyright
2005,
American Mathematical Society
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