Large and moderate deviations in testing Rayleigh diffusion model
Author:
Publisher
Springer Science and Business Media LLC
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Link
http://link.springer.com/content/pdf/10.1007/s00362-012-0450-5.pdf
Reference15 articles.
1. Bishwal JPN (2008a) Parameter estimation in stochastic differential equations. Lecture Notes in Mathematics, Vol 1923. Springer, Berlin
2. Bishwal JPN (2008b) Large deviations in testing fractional Ornstein-Uhlenbeck models. Stat Probab Lett 78: 953–962
3. Blahut RE (1984) Hypothesis testing and information theory. IEEE Trans Inf Theory 20: 405–415
4. Chiyonobu T (2003) Hypothesis testing for signal detection problem and large deviations. Nagoya Math J 162: 187–203
5. Dembo A, Zeitouni O (1998) Large deviations techniques and applications. Springer, New York
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2. Large and moderate deviations in testing Ornstein-Uhlenbeck process with linear drift;Frontiers of Mathematics in China;2016-01-14
3. Sequential Maximum Likelihood Estimation for the Parameter of the Linear Drift Term of the Rayleigh Diffusion Process;International Journal of Nonlinear Sciences and Numerical Simulation;2015-02-01
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5. Moderate Deviation for Parameter Estimation in the Rayleigh Diffusion Process;Communications in Statistics - Simulation and Computation;2014-01
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