Bridging the gap: A likelihood function approach for the analysis of ranking data
Bridging the gap: A likelihood function approach for the analysis of ranking data
复制标题
弥合差距：用于分析排名数据的似然函数方法
DOI：
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发表时间：
2016
期刊：
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通讯作者：
M. Alvo
中科院分区：
文献类型：
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作者：
M. Alvo
在参数设置中，似然函数的概念形成了假设检验和参数估计的基础。与方差分析有关的检验完全源于对似然函数的考虑。另一方面，非参数程序通常是在没有任何正式机制的情况下得出的，通常是聪明的直觉的结果。在本文中，我们提出了一种更正式的方法来派生涉及到等级使用的测试。具体地说，我们定义了一个由数据等级特征驱动的似然函数，并证明了这将导致众所周知的假设检验。我们还指出了进一步探索的各个领域，例如如何合并协变量。
ABSTRACT In the parametric setting, the notion of a likelihood function forms the basis for the development of tests of hypotheses and estimation of parameters. Tests in connection with the analysis of variance stem entirely from considerations of the likelihood function. On the other hand, non parametric procedures have generally been derived without any formal mechanism and are often the result of clever intuition. In the present article, we propose a more formal approach for deriving tests involving the use of ranks. Specifically, we define a likelihood function motivated by characteristics of the ranks of the data and demonstrate that this leads to well-known tests of hypotheses. We also point to various areas of further exploration such as how co-variates may be incorporated.