Estimation of exponential regerssion parameters using binary data
學年 81
學期 1
出版(發表)日期 1992-08-01
作品名稱 Estimation of exponential regerssion parameters using binary data
著者 Cheng, K.F.; Wu, Jong-wuu
單位 淡江大學統計學系
出版者 Philadelphia: Taylor & Francis Inc.
著錄名稱、卷期、頁數 Communications in Statistics: Theory and Methods 21(8), pp.2203-2214
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 ellipticaily symmetric distributions, for the explanatory variables, the estimators are 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 are 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.
關鍵字 Exponential regression;least square method;binary data;maximum likelihood estimate
語言 en
ISSN 0361-0926
期刊性質 國外
通訊作者 Cheng, K.F.; Wu, Jong-wuu
國別 USA
出版型式 紙本

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