On optimality of the LR tests in the sense of exact slopes. II. Application to individual distributions

František Rublík

Displaying similar documents to “On optimality of the LR tests in the sense of exact slopes. II. Application to individual distributions”

On two tests based on disjoint m-spacings

Franciszek Czekała (1998)

Applicationes Mathematicae

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This paper is concerned with the properties of two statistics based on the logarithms of disjoint m-spacings. The asymptotic normality is established in an elementary way and exact and asymptotic means and variances are computed in the case of uniform distribution on the interval [0,1]. This result is generalized to the case when the sample is drawn from a distribution with positive step density on [0,1]. Bahadur approximate efficiency of tests based on those statistics is found for...

Adaptive goodness-of-fit testing from indirect observations

Cristina Butucea, Catherine Matias, Christophe Pouet (2009)

Annales de l'I.H.P. Probabilités et statistiques

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In a convolution model, we observe random variables whose distribution is the convolution of some unknown density and some known noise density . We assume that is polynomially smooth. We provide goodness-of-fit testing procedures for the test : = , where the alternative is expressed with respect to $𝕃_{2}$ -norm (i.e. has the form $ψ_{n}^{- 2} {∥ f - f_{0} ∥}_{2}^{2} \geq 𝒞$ ). Our procedure is adaptive with respect to the unknown smoothness parameter of . Different testing rates ( ...

Some asymptotic results for robust procedures for testing the constancy of regression models over time

Marie Hušková (1990)

Kybernetika

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Reliability for Beta Models

Nadarajah, Saralees (2002)

Serdica Mathematical Journal

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In the area of stress-strength models there has been a large amount of work as regards estimation of the reliability R = Pr(X2 < X1 ) when X1 and X2 are independent random variables belonging to the same univariate family of distributions. The algebraic form for R = Pr(X2 < X1 ) has been worked out for the majority of the well-known distributions including Normal, uniform, exponential, gamma, weibull and pareto. However, there are still many other distributions for which the form...