论文标题
在对Beta分配的新测试中
On a new test of fit to the beta distribution
论文作者
论文摘要
我们建议基于有条件的时刻特征，为Beta分布家族提供了一个新的$ l^2 $ -type拟合测试。鉴定了渐近无效的分布，并且由于它取决于潜在的参数，因此提出了参数引导程序。显示了与满足收敛标准的所有替代方案的一致性，并且蒙特卡洛模拟研究表明，新程序的表现优于大多数经典测试。最后，该过程应用于与空气湿度有关的真实数据集。
We propose a new $L^2$-type goodness-of-fit test for the family of beta distributions based on a conditional moment characterisation. The asymptotic null distribution is identified, and since it depends on the underlying parameters, a parametric bootstrap procedure is proposed. Consistency against all alternatives that satisfy a convergence criterion is shown, and a Monte Carlo simulation study indicates that the new procedure outperforms most of the classical tests. Finally, the procedure is applied to a real data set related to air humidity.
