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Hypotheses testing for a multidimensional parameter of inhomogeneous Poisson processes

机译:对非均匀泊松过程的多维参数进行假设检验

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We observe a realization of an inhomogeneous Poisson process whose intensity function depends on an unknown multidimensional parameter. We consider the asymptotic behaviour of the Rao score test for a simple null hypothesis against the multilateral alternative. By using the Edgeworth type expansion (under the null hypothesis) for a vector of stochastic integrals with respect to the Poisson process, we refine the (classic) threshold of the test (obtained by the central limit theorem), which improves the first type probability of error. The expansion allows us to describe the power of the test under the local alternative, i.e. a sequence of alternatives, which converge to the null hypothesis with a certain rate. The rates can be different for components of the parameter.
机译:我们观察到一个不均匀的泊松过程的实现,其强度函数取决于未知的多维参数。我们考虑针对多边选择的简单零假设的Rao评分检验的渐近行为。通过对泊松过程的随机积分向量使用Edgeworth类型展开(在原假设下),我们细化了测试的(经典)阈值(由中心极限定理获得),从而提高了第一类概率错误。扩展使我们能够描述局部替代方案(即一系列替代方案)下的检验能力,这些替代方案以一定比率收敛于零假设。对于参数的组成部分,速率可以不同。

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