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New Directions in Time Series Analysis

E-BookPDF1 - PDF WatermarkE-Book
382 Seiten
Englisch
Springer New Yorkerschienen am06.12.20121993

Produkt

Details
Weitere ISBN/GTIN9781461392965
ProduktartE-Book
EinbandartE-Book
FormatPDF
Format Hinweis1 - PDF Watermark
FormatE107
Erscheinungsjahr2012
Erscheinungsdatum06.12.2012
Auflage1993
Reihen-Nr.46
Seiten382 Seiten
SpracheEnglisch
IllustrationenXVIII, 382 p.
Artikel-Nr.8783311
Rubriken
Genre9200

Inhalt/Kritik

Inhaltsverzeichnis
Recent developments in location estimation and regression for long-memory processes.- Phase-transition in statistical physical models with discrete and continuous symmetries.- Identification of linear systems from noisy data.- Unit roots in U.S. macroeconomic time series: A survey of classical and Bayesian perspectives.- A nonparametric approach to nonlinear time series analysis: Estimation and simulation.- Asymptotics of predictive stochastic complexity.- Smoothness priors.- An extension of quadrature-based methods for solving Euler conditions.- Long memory shot noises and limit theorems with application to Burgers' equation.- On approximate modeling of linear Gaussian processes.- On the identification and prediction of nonlinear models.- Identification of stochastic time-varying parameters.- Convergence of Aström-Wittenmark's self-tuning regulator and related topics.- On the closure of several sets of ARMA and linear state space models with a given structure.- Weak convergence to self-affine processes in dynamical systems.- Recursive estimation in ARMAX models.- On adaptive stabilization and ergodic behaviour of systems with Jump-Markov parameters via nonlinear filtering.- The convergence of output error recursions in infinite order moving average noise.- Linear models with long-range dependence and with finite or infinite variance.- Posterior analysis of possibly integrated time series with an application to real GNP.- On network structure function computations.- Asymptotic properties of estimates in incorrect ARMA models for long-memory time series.mehr

Autor