SULJE VALIKKO

avaa valikko

Sequential Change Detection and Hypothesis Testing - General Non-i.i.d. Stochastic Models and Asymptotically Optimal Rules
188,10 €
Taylor & Francis Inc
Sivumäärä: 320 sivua
Asu: Kovakantinen kirja
Julkaisuvuosi: 2019, 02.12.2019 (lisätietoa)
Kieli: Englanti
How can major corporations and governments more quickly and accurately detect and address cyberattacks on their networks? How can local authorities improve early detection and prevention of epidemics? How can researchers improve the identification and classification of space objects in difficult (e.g., dim) settings?

These questions, among others in dozens of fields, can be addressed using statistical methods of sequential hypothesis testing and changepoint detection. This book considers sequential changepoint detection for very general non-i.i.d. stochastic models, that is, when the observed data is dependent and non-identically distributed. Previous work has primarily focused on changepoint detection with simple hypotheses and single-stream data. This book extends the asymptotic theory of change detection to the case of composite hypotheses as well as for multi-stream data when the number of affected streams is unknown. These extensions are more relevant for practical applications, including in modern, complex information systems and networks. These extensions are illustrated using Markov, hidden Markov, state-space, regression, and autoregression models, and several applications, including near-Earth space informatics and cybersecurity are discussed.

This book is aimed at graduate students and researchers in statistics and applied probability who are familiar with complete convergence, Markov random walks, renewal and nonlinear renewal theories, Markov renewal theory, and uniform ergodicity of Markov processes.

Key features:






Design and optimality properties of sequential hypothesis testing and change detection algorithms (in Bayesian, minimax, pointwise, and other settings)



Consideration of very general non-i.i.d. stochastic models that include Markov, hidden Markov, state-space linear and non-linear models, regression, and autoregression models



Multiple decision-making problems, including quickest change detection-identification



Real-world applications to object detection and tracking, near-Earth space informatics, computer network surveillance and security, and other topics

Tuotetta lisätty
ostoskoriin kpl
Siirry koriin
LISÄÄ OSTOSKORIIN
Tilaustuote | Arvioimme, että tuote lähetetään meiltä noin 1-3 viikossa. | Tilaa jouluksi viimeistään 27.11.2024. Tuote ei välttämättä ehdi jouluksi.
Myymäläsaatavuus
Helsinki
Tapiola
Turku
Tampere
Sequential Change Detection and Hypothesis Testing - General Non-i.i.d. Stochastic Models and Asymptotically Optimal Ruleszoom
Näytä kaikki tuotetiedot
Sisäänkirjautuminen
Kirjaudu sisään
Rekisteröityminen
Oma tili
Omat tiedot
Omat tilaukset
Omat laskut
Lisätietoja
Asiakaspalvelu
Tietoa verkkokaupasta
Toimitusehdot
Tietosuojaseloste