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多重不等式假设检验的平滑指示函数方法AI 解读

This paper proposes a class of origin-smooth approximators of indicators underlying the sum-of-negative-part statistic for testing multiple inequalities. The need for simulation or bootstrap to obtain test critical values is thereby obviated. A simple procedure is enabled using fixed critical values. The test is shown to have correct asymptotic size in the uniform sense that supremum finite-sample rejection probability over null-restricted data distributions tends…

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检验非嵌套假设的 Cox 修正似然比统计量的渐近局部结构AI 解读

It is shown that the Cox modified likelihood-ratio statistic for testing partially non-nested hypotheses H 0 and H 1 is asymptotically equivalent to a bilinear form in nondegenerate asymptotically normal random vectors for sequences of data-generating processes converging to the intersection of H 0 and H 1 but not necessarily belonging to either H 0 or H 1 . One of the asymptotically normal vectors is the complete parametric encompassing vector of Mizon and Richard, while…

检验非线性隐式约束与过度识别约束的广义 Wald 方法AI 解读

The Wald approach to testing direct explicit restrictions on a parameter vector is generalized to the case of nonlinear implicit constraints. When applied to subsystems of simultaneous equations models, the generalization enables the symmetric joint testing of nonlinear overidentifying structural restrictions under very wide conditions. By varying the choices of certain matrices used to construct the generalized Wald statistic, one produces a whole class of tests which have…

线性计量模型中的一类参数异方差检验AI 解读

A class of parametric for heteroscedasticity in linear models is discussed. For models with nonstochastic regressors, new exact within this class are suggested which utilize existing tables of the distribution of the von Neumann ratio and of the Durbin-Watson bounding ratios. Bound tests for heteroscedasticity in least squares regression are proposed. A rigorous treatment of within this class for heteroscedasticity in the errors of structural relations in dynamic…

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