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Ingster, Yu.I. and Suslina, I.A. (2003) Nonparametric Goodness-of-Fit Testing Under Gaussian Models. Springer-Verlag, New York.
https://doi.org/10.1007/978-0-387-21580-8

has been cited by the following article:

• TITLE: Kolmogorov-Smirnov APF Test for Inhomogeneous Poisson Processes with Shift Parameter

  AUTHORS: E. D. Wandji Tanguep, D. A. Njamen Njomen

  KEYWORDS: Inhomogeneous Poisson Process, Kolmogorov-Smirnov Type Test, Parametric Basic Hypothesis, Asymptotic Parameter Free Test, Shift Parameter

  JOURNAL NAME: Applied Mathematics, Vol.12 No.4, April 28, 2021

  ABSTRACT: In this article, we study the Kolmogorov-Smirnov type goodness-of-fit test for the inhomogeneous Poisson process with the unknown translation parameter as multidimensional parameter. The basic hypothesis and the alternative are composite and carry to the intensity measure of inhomogeneous Poisson process and the intensity function is regular. For this model of shift parameter, we propose test which is asymptotically partially distribution free and consistent. We show that under null hypothesis the limit distribution of this statistic does not depend on unknown parameter.