淡江大學機構典藏:Item 987654321/69190
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    題名: Estimation of exponential regerssion parameters using binary data
    作者: Cheng, K.F.;Wu, Jong-wuu
    貢獻者: 淡江大學統計學系
    關鍵詞: Exponential regression;least square method;binary data;maximum likelihood estimate
    日期: 1992-08
    上傳時間: 2013-05-31 11:38:36 (UTC+8)
    出版者: Philadelphia: Taylor & Francis Inc.
    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.
    關聯: Communications in Statistics: Theory and Methods 21(8), pp.2203-2214
    DOI: 10.1080/03610929208830907
    顯示於類別:[統計學系暨研究所] 期刊論文

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