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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/75110

    Title: Efficient Prediction Interval in Log-Normal Linear Model
    Authors: Chen, Li-Ching;Chen, Li-Hsueh;Ting, Chuan-Wei
    Contributors: 淡江大學統計學系
    Keywords: Log-normal linear model;Maximum likelihood;Ordinary least squares;Prediction interval
    Date: 2012-06
    Issue Date: 2012-03-13 01:55:20 (UTC+8)
    Publisher: ICIC International
    Abstract: 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.
    Relation: ICIC Express Letters 6(6), pp.1441-1445
    Appears in Collections:[統計學系暨研究所] 期刊論文

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