Titlebook: Nonparametric Statistics; 4th ISNPS, Salerno, Michele La Rocca,Brunero Liseo,Luigi Salmaso Conference proceedings 2020 Springer Nature Swi

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2194-1009 zation, and its international conferences are intended to foster the exchange of ideas and the latest advances and trends among researchers from around the world and to develop and disseminate nonparametric sta978-3-030-57308-9978-3-030-57306-5Series ISSN 2194-1009 Series E-ISSN 2194-1017

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Goodness-of-fit Test for the Baseline Hazard Rate,t statistic is given by an optimal estimator of the quadratic functional of the same function. Our test procedure attains the rate . over Besov classes of functions ., ., which is known to be minimax optimal in the context of testing the intensity function of a Poisson processes.

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Kernel Circular Deconvolution Density Estimation,in a kernel-type estimator with weight functions that are reminiscent of deconvolution kernels. Here, differently from the Euclidean setting, discrete Fourier coefficients are involved rather than characteristic functions. We provide some simulation results along with a real data application.

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978-3-030-57308-9Springer Nature Switzerland AG 2020

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Nonparametric Statistics978-3-030-57306-5Series ISSN 2194-1009 Series E-ISSN 2194-1017

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https://doi.org/10.1007/978-3-030-57306-5nonparametric statistics; semiparametric statistics; dependent data; nonparametric curve estimation; per

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Change of Measure Applications in Nonparametric Statistics,r the null hypothesis. Hoeffding introduced a change of measure formula for the ranks of the observed data which led to obtaining locally most powerful rank tests. In this paper, we review these methods and propose a new approach which leads on the one hand to new derivations of existing statistics.