ESTIMATION OF EXPONENTIAL REGRESSION PARAMETERS USING BINARY DATA

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题名:	ESTIMATION OF EXPONENTIAL REGRESSION PARAMETERS USING BINARY DATA
作者:	CHENG,KF;WU,JW
贡献者:	統計研究所
日期:	1992
上传时间:	2010-06-29 19:34:44 (UTC+8)
出版者:	中央大學
摘要:	Exponential regression model is important in analyzing data from heterogeneous populations. In this paper we propose a simple method to estimate the regression parameters using binary data. Under certain design distributions, including elliptically symmetric distributions, for the explanatory variables, the estimators axe shown to be consistent and asymptotically normal when sample size is large. For finite samples, the new estimates were shown to behave reasonably well. They axe competitive with the maximum likelihood estimates and more importantly, according to our simulation results, the cost of CPU time for computing new estimates is only 1/7 of that required for computing the usual maximum likelihood estimates. We expect the savings in CPU time would be more dramatic with larger dimension of the regression parameter space.
關聯:	COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
显示于类别:	[統計研究所] 期刊論文

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