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摘要翻译：
本文讨论了在[0,1)，(0,1]或[0,1]区间内观测到的分数数据的建模问题。提出了连续-离散混合分布。贝塔分布被用来描述模型的连续分量，因为它的密度可以有相当不同的形状，这取决于指示分布的两个参数的值。研究了所提出的分布的性质。讨论了极大似然估计和矩量估计方法。最后给出了利用真实数据的实际应用。
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英文标题：
《Inflated Beta Distributions》
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作者：
Raydonal Ospina and Silvia L. P. Ferrari
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最新提交年份：
2007
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分类信息：
一级分类：Statistics 统计学
二级分类：Methodology 方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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英文摘要：
This paper considers the issue of modeling fractional data observed in the interval [0,1), (0,1] or [0,1]. Mixed continuous-discrete distributions are proposed. The beta distribution is used to describe the continuous component of the model since its density can have quite diferent shapes depending on the values of the two parameters that index the distribution. Properties of the proposed distributions are examined. Also, maximum likelihood and method of moments estimation is discussed. Finally, practical applications that employ real data are presented.
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PDF链接：
https://arxiv.org/pdf/705.07
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