Assume that we have a random sample from an absolutely continuous distribution (univariate, or multivariate) with a known functional form and some unknown parameters. In this paper, we have studied several parametric tests based on statistics that are symmetric functions of $m$-step disjoint sample spacings. Asymptotic properties of these tests have been investigated under the simple null hypothesis and under a sequence of local alternatives converging to the null hypothesis. The asymptotic properties of the proposed tests have also been studied under the composite null hypothesis. We observed that these tests have similar asymptotic properties as the likelihood ratio test. Finite sample performances of the proposed tests are assessed numerically. A data analysis based on real data is also reported. The proposed tests provide alternative to similar tests based on simple spacings (i.e., $m=1$), that were proposed earlier in the literature. These tests also provide an alternative to likelihood ratio tests in situations where likelihood function may be unbounded and hence, likelihood ratio tests do not exist.
翻译:假设我们有一个来自绝对连续分布(单变或多变)的随机样本,该样本具有已知功能形式和一些未知参数。在本文中,我们研究了基于对称函数的数项参数测试,即分步脱节的样本间距。这些测试的非抽取特性在简单的空假设和与无效假设相融合的一系列当地替代品下进行了调查。还根据综合无效假设研究了拟议测试的无抽取特性。我们观察到,这些测试与概率比测试相似。对拟议测试的精度样本性能进行了数字评估。还报告了基于真实数据的数据分析。拟议的测试提供了基于文献早先提出的简单间距(即1美元=1美元)的类似测试的替代方法。这些测试还提供了一种替代可能性比率测试的替代方法,在概率功能可能不受约束的情况下,因此不存在概率比测试。