Dependence in Probability and Statistics

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This volume collects recent works on weakly dependent, long-memory and multifractal processes and introduces new dependence measures for studying complex stochastic systems. Other topics include the statistical theory for bootstrap and permutation statistics for infinite variance processes, the depe...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Doukhan, Paul (Editor ), Lang, Gabriel (Editor ), Surgailis, Donatas (Editor ), Teyssière, Gilles (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010.
Edición:1st ed. 2010.
Colección:Lecture Notes in Statistics, 200
Temas:
Probabilities.
Mathematics > Data processing.
Mathematical statistics > Data processing.
Statistics .
Probability Theory.
Computational Mathematics and Numerical Analysis.
Statistics and Computing.
Statistical Theory and Methods.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Permutation and bootstrap statistics under infinite variance
  • Max-Stable Processes: Representations, Ergodic Properties and Statistical Applications
  • Best attainable rates of convergence for the estimation of the memory parameter
  • Harmonic analysis tools for statistical inference in the spectral domain
  • On the impact of the number of vanishing moments on the dependence structures of compound Poisson motion and fractional Brownian motion in multifractal time
  • Multifractal scenarios for products of geometric Ornstein-Uhlenbeck type processes
  • A new look at measuring dependence
  • Robust regression with infinite moving average errors
  • A note on the monitoring of changes in linear models with dependent errors
  • Testing for homogeneity of variance in the wavelet domain.

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