We consider the problem of maximum likelihood estimation of logistic sinusoidal regression models and develop some asymptotic theory including the consistency and joint rates of convergence for the maximum likelihood estimators. The key techniques build upon a synthesis of the results of Walker and Song and Li for the widely studied sinusoidal regression model and on making a connection to a result of Radchenko. Monte Carlo simulations are also presented to demonstrate the finite-sample performance of the estimators
Identifer | oai:union.ndltd.org:unt.edu/info:ark/67531/metadc407796 |
Date | 12 1900 |
Creators | Weng, Yu |
Contributors | Song, Kai-Sheng, Allaart, Pieter C., Wang, Jiaping |
Publisher | University of North Texas |
Source Sets | University of North Texas |
Language | English |
Detected Language | English |
Type | Thesis or Dissertation |
Format | Text |
Rights | Public, Weng, Yu, Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved. |
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