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Cálculo de la distribución del tiempo de vida de componentes mediante autopsia en sistemas binarios aditivos, serie-paralelo y paralelo-serie.

Fermín Mallor Giménez, Cristina Azcárate Camio, Antonio Pérez Prados (1997)

Qüestiió

En este artículo se estudia el problema de determinar la función de distribución del tiempo de vida de las componentes de un sistema binario, a partir del conocimiento de las leyes que rigen el funcionamiento del sistema y del conjunto de componentes que causa su fallo (obtenida mediante autopsia del sistema en el momento de su deterioro).Se presentan los resultados de Meilijson (1981) y Nowik (1990) que proponen un sistema de ecuaciones implícito para obtener estas distribuciones. Sin embargo,...

Challenging the empirical mean and empirical variance: A deviation study

Olivier Catoni (2012)

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

We present new M-estimators of the mean and variance of real valued random variables, based on PAC-Bayes bounds. We analyze the non-asymptotic minimax properties of the deviations of those estimators for sample distributions having either a bounded variance or a bounded variance and a bounded kurtosis. Under those weak hypotheses, allowing for heavy-tailed distributions, we show that the worst case deviations of the empirical mean are suboptimal. We prove indeed that for any confidence level, there...

Change-point estimation from indirect observations. 1. Minimax complexity

A. Goldenshluger, A. Juditsky, A. B. Tsybakov, A. Zeevi (2008)

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

We consider the problem of nonparametric estimation of signal singularities from indirect and noisy observations. Here by singularity, we mean a discontinuity (change-point) of the signal or of its derivative. The model of indirect observations we consider is that of a linear transform of the signal, observed in white noise. The estimation problem is analyzed in a minimax framework. We provide lower bounds for minimax risks and propose rate-optimal estimation procedures.

Change-point estimation from indirect observations. 2. Adaptation

A. Goldenshluger, A. Juditsky, A. Tsybakov, A. Zeevi (2008)

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

We focus on the problem of adaptive estimation of signal singularities from indirect and noisy observations. A typical example of such a singularity is a discontinuity (change-point) of the signal or of its derivative. We develop a change-point estimator which adapts to the unknown smoothness of a nuisance deterministic component and to an unknown jump amplitude. We show that the proposed estimator attains optimal adaptive rates of convergence. A simulation study demonstrates reasonable practical...

Change-point problems: A Bayesian nonparametric approach

Pietro Muliere, Marco Scarsini (1985)

Aplikace matematiky

A change-point problem is examined from a Bayesian viewpoint, under nonparametric hypotheses. A Ferguson-Dirichlet prior is chosen and the posterior distribution is computed for the change-point and for the unknown distribution functions.

Comparison at optimal levels of classical tail index estimators: a challenge for reduced-bias estimation?

M. Ivette Gomes, Lígia Henriques-Rodrigues (2010)

Discussiones Mathematicae Probability and Statistics

In this article, we begin with an asymptotic comparison at optimal levels of the so-called "maximum likelihood" (ML) extreme value index estimator, based on the excesses over a high random threshold, denoted PORT-ML, with PORT standing for peaks over random thresholds, with a similar ML estimator, denoted PORT-MP, with MP standing for modified-Pareto. The PORT-MP estimator is based on the same excesses, but with a trial of accommodation of bias on the Generalized Pareto model underlying those excesses....

Comparison of two methods for approximation of probability distributions with prescribed marginals

Albert Pérez, Milan Studený (2007)

Kybernetika

Let P be a discrete multidimensional probability distribution over a finite set of variables N which is only partially specified by the requirement that it has prescribed given marginals { P A ; A ∈ 𝒮 } , where 𝒮 is a class of subsets of N with ⋃ 𝒮 = N . The paper deals with the problem of approximating P on the basis of those given marginals. The divergence of an approximation P ^ from P is measured by the relative entropy H ( P | P ^ ) . Two methods for approximating P are compared. One of them uses formerly introduced concept of...

Concept of Data Depth and Its Applications

Ondřej Vencálek (2011)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

Data depth is an important concept of nonparametric approach to multivariate data analysis. The main aim of the paper is to review possible applications of the data depth, including outlier detection, robust and affine-equivariant estimates of location, rank tests for multivariate scale difference, control charts for multivariate processes, and depth-based classifiers solving discrimination problem.

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