The Performance of Some Rough Tests for Bivariate Normality Before and After Coordinate Transformations to Normality
The Performance of Some Rough Tests for Bivariate Normality Before and After Coordinate Transformations to Normality
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坐标变换为正态性之前和之后双变量正态性的一些粗略测试的性能
DOI：
10.1080/00401706.1970.10488694
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发表时间：
1970
期刊：
影响因子：
2.5
通讯作者：
C. Kowalski
中科院分区：
文献类型：
--
作者：
C. Kowalski
一些粗略的二元正态性测试，试图量化的直观概念，坐标变换的正态性产生的分布是“更多的二元正态”比原来的变量。这些测试不是严格的程序，但直观上是令人满意的，基于自然统计，并提供了从正态模型的二元分布的“距离”的数值测量。研究表明，对于广泛的非正态（X，Y）分布，坐标变换到正态分布会减少这些检验测量的该距离。它表明如何可以估计的坐标变换和相关理论的应用进行了探讨。
Some rough tests for bivariate normality are employed in an attempt to quantify the intuitive notion that coordinate transformations to normality produce distributions which are “more bivariate normal” than the original variables. These tests are not rigorous procedures but are intuitively satisfying, based on natural statistics, and provide numerical measures of the “distance” of a bivariate distribution from the normal model. It is shown that, for a wide class of non-normal (X, Y) distributions, coordinate transformations to normality decrease this distance as measured by these tests. It is indicated how one may estimate the coordinate transformations and applications to correlation theory are explored.