淡江大學機構典藏:Item 987654321/75110
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    题名: Efficient Prediction Interval in Log-Normal Linear Model
    作者: Chen, Li-Ching;Chen, Li-Hsueh;Ting, Chuan-Wei
    贡献者: 淡江大學統計學系
    关键词: Log-normal linear model;Maximum likelihood;Ordinary least squares;Prediction interval
    日期: 2012-06
    上传时间: 2012-03-13 01:55:20 (UTC+8)
    出版者: ICIC International
    摘要: Log-normal linear models are widely applied, and in many situations one is interested in predicting the response variable at the original scale for given covariate values. The back-transform (BT) prediction interval is universally used in practice. This study constructs a prediction interval of the response variable based on the highest density (HD) of the log-normal distribution. The simulation results show that the HD prediction intervals have reasonable coverage rates and indeed improve the intervals' length over the BT prediction intervals, particularly for the cases of small sample sizes. An example is used to illustrate the implementation of the HD prediction interval.
    關聯: ICIC Express Letters 6(6), pp.1441-1445
    显示于类别:[統計學系暨研究所] 期刊論文

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