Author: Patrick Billingsley
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Statistical Inference for Markov Processes, Reprinted
Author: Patrick Billingsley
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Statistical Inference for Markov Processes
Author: Patrick Billingsley
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 100
Book Description
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 100
Book Description
Statistical Inference for Piecewise-deterministic Markov Processes
Author: Romain Azais
Publisher: John Wiley & Sons
ISBN: 1119544033
Category : Mathematics
Languages : en
Pages : 279
Book Description
Piecewise-deterministic Markov processes form a class of stochastic models with a sizeable scope of applications: biology, insurance, neuroscience, networks, finance... Such processes are defined by a deterministic motion punctuated by random jumps at random times, and offer simple yet challenging models to study. Nevertheless, the issue of statistical estimation of the parameters ruling the jump mechanism is far from trivial. Responding to new developments in the field as well as to current research interests and needs, Statistical inference for piecewise-deterministic Markov processes offers a detailed and comprehensive survey of state-of-the-art results. It covers a wide range of general processes as well as applied models. The present book also dwells on statistics in the context of Markov chains, since piecewise-deterministic Markov processes are characterized by an embedded Markov chain corresponding to the position of the process right after the jumps.
Publisher: John Wiley & Sons
ISBN: 1119544033
Category : Mathematics
Languages : en
Pages : 279
Book Description
Piecewise-deterministic Markov processes form a class of stochastic models with a sizeable scope of applications: biology, insurance, neuroscience, networks, finance... Such processes are defined by a deterministic motion punctuated by random jumps at random times, and offer simple yet challenging models to study. Nevertheless, the issue of statistical estimation of the parameters ruling the jump mechanism is far from trivial. Responding to new developments in the field as well as to current research interests and needs, Statistical inference for piecewise-deterministic Markov processes offers a detailed and comprehensive survey of state-of-the-art results. It covers a wide range of general processes as well as applied models. The present book also dwells on statistics in the context of Markov chains, since piecewise-deterministic Markov processes are characterized by an embedded Markov chain corresponding to the position of the process right after the jumps.
Statistical Inference for Markov Processes
Author: Walter F. Johnson
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Statistical Inferences for Markov Processes
Author: Patrick Billingsley
Publisher:
ISBN:
Category :
Languages : en
Pages : 75
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 75
Book Description
Statistical Inference for Markov Processes C.Patrick Billingsley
Author: Patrick Billingsley
Publisher:
ISBN:
Category :
Languages : en
Pages : 75
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 75
Book Description
Inference in Hidden Markov Models
Author: Olivier Cappé
Publisher: Springer Science & Business Media
ISBN: 0387289828
Category : Mathematics
Languages : en
Pages : 656
Book Description
This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Many examples illustrate the algorithms and theory. This book builds on recent developments to present a self-contained view.
Publisher: Springer Science & Business Media
ISBN: 0387289828
Category : Mathematics
Languages : en
Pages : 656
Book Description
This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Many examples illustrate the algorithms and theory. This book builds on recent developments to present a self-contained view.
Some Aspects of Statistical Inference for M-th Order Markov Processes
Author: Ramanpillai Krishna Pillai
Publisher:
ISBN:
Category :
Languages : en
Pages : 58
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 58
Book Description
Statistical Inference in Markov Chains Using the Principal of Minimum Discrimination Information
Author: Said Mohamed Rujbani
Publisher:
ISBN:
Category : Markov processes
Languages : en
Pages : 226
Book Description
Publisher:
ISBN:
Category : Markov processes
Languages : en
Pages : 226
Book Description
Statistical Inference on Aggregated Markov Processes
Author: Wenyu Wang
Publisher:
ISBN:
Category : Markov processes
Languages : en
Pages : 128
Book Description
Publisher:
ISBN:
Category : Markov processes
Languages : en
Pages : 128
Book Description