Study on Probability Plot Correlation Coefficient of the Log-Weibull Distribution  

作　　者：蒋仁言 

机构地区：[1]Faculty of Automotive and Mechanical Engineering, Changsha University of Science and Technology

出　　处：《Journal of Shanghai Jiaotong university(Science)》2015年第3期298-301,共4页上海交通大学学报（英文版）

基　　金：the National Natural Science Foundation of China(No.71371035)

摘　　要：The log-Weibull distribution is a variant of the three-parameter Weibull distribution. The probability plot of a distribution model is desired since it can help to decide on whether the model is appropriate for fitting a given dataset and can provide the initial estimate of the model parameters. The decision on the appropriateness of a distribution is somehow subjective. This paper presents a probability plot of the log-Weibull distribution(LWPP). The distribution of the probability plot correlation coefficient is studied. From this distribution, a lower confidence limit is determined for determining whether the probability plot correlation coefficient derived from a given data set is large enough. The appropriateness and usefulness of this study are illustrated by two real-world examples.The log-Weibull distribution is a variant of the three-parameter Weibull distribution. The probability plot of a distribution model is desired since it can help to decide on whether the model is appropriate for fitting a given dataset and can provide the initial estimate of the model parameters. The decision on the appropriateness of a distribution is somehow subjective. This paper presents a probability plot of the log-Weibull distribution （LWPP）. The distribution of the probability plot correlation coefficient is studied. From this distribution, a lower confidence limit is determined for determining whether the probability plot correlation coefficient derived from a given data set is large enough. The appropriateness and usefulness of this study are illustrated by two real-world examples.

关 键 词：log-Weibull probability plot correlation coefficient lower confidence limit 

分 类 号：O213.2[理学—概率论与数理统计]