Nonlinear hypotheses, inequality restrictions, and non-nested hypotheses: exact simultaneous tests in linear regressions
Nonlinear hypotheses, inequality restrictions, and non-nested hypotheses: exact simultaneous tests in linear regressions
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非线性假设、不等式限制和非嵌套假设：线性回归中的精确同时检验
DOI：
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发表时间：
1989
期刊：
影响因子：
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通讯作者：
Jean
中科院分区：
文献类型：
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作者：
Jean
在经典线性模型的背景下，考虑了两个任意假设的回归系数的比较问题。涉及非线性假设，不等式限制，或非嵌套假设的问题包括作为特殊情况。给出了似然比统计量零分布的精确界。在一个重要的特殊情况下，提出了一种类似于Durbin-Watson检验的边界检验。还研究了多重测试问题
In the context of the classical linear model, the problem of comparing two arbitrary hypotheses on the regression coefficients is considered. Problems involving nonlinear hypotheses, inequality restrictions, or non-nested hypotheses are included as special cases. Exact bounds on the null distribution of likelihood ratio statistics are derived. In an important special case, a bounds test similar to the Durbin-Watson test is proposed. Multiple testing problems are also studied