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基于信息增益的正态模型与指数模型依赖度量
The principle of obtaining a measure of dependence based on the notion of information gain is examined for normal models and for several bivariate exponential models. It is shown that, under normal models, the principle usually gives good measures. It is also shown that it gives interesting measures for some exponential models.
基于信息增益的正态模型与指数模型依赖度量
The principle of obtaining a measure of dependence based on the notion of information gain is examined for normal models and for several bivariate exponential models. It is shown that, under normal models, the principle usually gives good measures. It is also shown that it gives interesting measures for some exponential models.
用于独立性检验的类内秩检验
An intraclass rank test of Spearman type is proposed to test for independence in a bivariate population. The test is useful when there is prior information that the population has the same marginal distributions. It is shown that the proposed test is asymptotically equivalent to Spearman's test under the null hypothesis of independence and its contiguous alternatives and is empirically better than that in the case of small sample sizes.
An intraclass rank test of Spearman type is proposed to test for independence in a bivariate population. The test is useful when there is prior information that the population has the same marginal distributions. It is shown that the proposed test is asymptotically equivalent to Spearman's test under the null hypothesis of independence and its contiguous alternatives and is empirically better than that in the case of small sample sizes.
二元正态分布单侧检验的一种方法
In this paper we propose a new test procedure for a one-sided alternative concerning the mean vector in a bivariate normal population with known covariance matrix. The problem was investigated by Kudü (1963) with the likelihood ratio criterion, while our procedure is derived from a new principle. The principle will be useful for many testing problems. Monte Carlo results are given showing that our procedure is more powerful when the population correlation is negative. In…
二元正态分布中单侧检验的一种方法
In this paper we propose a new test procedure for a one-sided alternative concerning the mean vector in a bivariate normal population with known covariance matrix. The problem was investigated by Kudü (1963) with the likelihood ratio criterion, while our procedure is derived from a new principle. The principle will be useful for many testing problems. Monte Carlo results are given showing that our procedure is more powerful when the population correlation is negative. In…
线性模型中的偏相关检验
Two asymptotically distribution-free tests of partial correlation in a trivariate linear model are proposed. The model includes two nuisance parameters, and the tests use modified varsions of Kendall's and Spearman's correlation coefficients for transformed values of the observations, where the transformation is chosen to eliminate the nuisance parameters by using consistent estimators of them. Some arguments about the asymptotic properties of the statistics and computer…
线性模型中的偏相关检验
Two asymptotically distribution-free tests of partial correlation in a trivariate linear model are proposed. The model includes two nuisance parameters, and the tests use modified varsions of Kendall's and Spearman's correlation coefficients for transformed values of the observations, where the transformation is chosen to eliminate the nuisance parameters by using consistent estimators of them. Some arguments about the asymptotic properties of the statistics and computer…