Transformation Approaches for the Construction of Weibull Prediction Interval
Two methods of transforming the Weibull data to near normality, namely the Box-Cox method and Kullback-Leibler (KL) information method, are discussed and contrasted. A simple prediction interval (PI) based on the better KL information method is proposed. The asymptotic property of this interval is e...
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sg-smu-ink.soe_research-11952018-05-07T06:48:56Z Transformation Approaches for the Construction of Weibull Prediction Interval YANG, Zhenlin SEE, Stanley P. XIE, Min Two methods of transforming the Weibull data to near normality, namely the Box-Cox method and Kullback-Leibler (KL) information method, are discussed and contrasted. A simple prediction interval (PI) based on the better KL information method is proposed. The asymptotic property of this interval is established. Its small sample behavior is investigated using Monte Carlo simulation. Simulation results show that this simple interval is close to the existing complicated PI where the percentage points of the reference distribution have to be either simulated or approximated. 2003-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/196 info:doi/10.1016/s0167-9473(02)00232-3 https://ink.library.smu.edu.sg/context/soe_research/article/1195/viewcontent/Transformation_Weibull_prediction_2003.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Box-Cox transformation Coverage probability Kullback-Leibler information Prediction interval Weibull distribution Econometrics |
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Box-Cox transformation Coverage probability Kullback-Leibler information Prediction interval Weibull distribution Econometrics |
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Box-Cox transformation Coverage probability Kullback-Leibler information Prediction interval Weibull distribution Econometrics YANG, Zhenlin SEE, Stanley P. XIE, Min Transformation Approaches for the Construction of Weibull Prediction Interval |
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Two methods of transforming the Weibull data to near normality, namely the Box-Cox method and Kullback-Leibler (KL) information method, are discussed and contrasted. A simple prediction interval (PI) based on the better KL information method is proposed. The asymptotic property of this interval is established. Its small sample behavior is investigated using Monte Carlo simulation. Simulation results show that this simple interval is close to the existing complicated PI where the percentage points of the reference distribution have to be either simulated or approximated. |
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YANG, Zhenlin SEE, Stanley P. XIE, Min |
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YANG, Zhenlin SEE, Stanley P. XIE, Min |
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YANG, Zhenlin |
title |
Transformation Approaches for the Construction of Weibull Prediction Interval |
title_short |
Transformation Approaches for the Construction of Weibull Prediction Interval |
title_full |
Transformation Approaches for the Construction of Weibull Prediction Interval |
title_fullStr |
Transformation Approaches for the Construction of Weibull Prediction Interval |
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Transformation Approaches for the Construction of Weibull Prediction Interval |
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transformation approaches for the construction of weibull prediction interval |
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Institutional Knowledge at Singapore Management University |
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2003 |
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https://ink.library.smu.edu.sg/soe_research/196 https://ink.library.smu.edu.sg/context/soe_research/article/1195/viewcontent/Transformation_Weibull_prediction_2003.pdf |
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