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Displaying similar documents to “Goodness-of-fit test for long range dependent processes”

Adaptive tests of qualitative hypotheses

Yannick Baraud, Sylvie Huet, Béatrice Laurent (2003)

ESAIM: Probability and Statistics

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We propose a test of a qualitative hypothesis on the mean of a n -gaussian vector. The testing procedure is available when the variance of the observations is unknown and does not depend on any prior information on the alternative. The properties of the test are non-asymptotic. For testing positivity or monotonicity, we establish separation rates with respect to the euclidean distance, over subsets of ℝ n which are related to Hölderian balls in functional spaces. We provide a simulation...

Goodness-of-fit test for long range dependent processes

Gilles Fay, Anne Philippe (2010)

ESAIM: Probability and Statistics

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In this paper, we make use of the information measure introduced by Mokkadem (1997) for building a goodness-of-fit test for long-range dependent processes. Our test statistic is performed in the frequency domain and writes as a non linear functional of the normalized periodogram. We establish the asymptotic distribution of our statistic under the null hypothesis. Under specific alternative hypotheses, we prove that the power converges to one. The performance of our test procedure is illustrated...

Adaptive tests for periodic signal detection with applications to laser vibrometry

Magalie Fromont, Céline Lévy-leduc (2006)

ESAIM: Probability and Statistics

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Initially motivated by a practical issue in target detection laser vibrometry, we are interested in the problem of periodic signal detection in a Gaussian fixed design regression framework. Assuming that the signal belongs to some periodic Sobolev ball and that the variance of the noise is known, we first consider the problem from a minimax point of view: we evaluate the so-called which corresponds to the minimal distance between the signal and zero so that the detection...

A class of tests for exponentiality based on a continuum of moment conditions

Simos G. Meintanis (2009)

Kybernetika

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The empirical moment process is utilized to construct a family of tests for the null hypothesis that a random variable is exponentially distributed. The tests are consistent against the 'new better than used in expectation' (NBUE) class of alternatives. Consistency is shown and the limit null distribution of the test statistic is derived, while efficiency results are also provided. The finite-sample properties of the proposed procedure in comparison to more standard procedures are investigated...