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Statistical Topics and Stochastic Models for Dependent Data With Applications 1st edition

Name: Statistical Topics and Stochastic Models for Dependent Data With Applications 1st edition
SKU: EB-14463402
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Statistical Topics and Stochastic Models for Dependent Data With Applications Vlad Stefan Barbu Digital Instant Download

Author(s): Vlad Stefan Barbu, Nicolas Vergne

ISBN(s): 9781119779414, 1119779413

File Details: PDF, 4.13 MB

Year: 2020

Language: English

SKU: EB-14463402 Category: Uncategorized Tags: Nicolas Vergne, Vlad Stefan Barbu

Description

Statistical Topics and Stochastic Models for Dependent Data With Applications 1st edition- Ebook Instant Download/Delivery ISBN(s): 9781119779414,1119779413,9781119779407

Product details:

ISBN 13: 9781119779407
Author:Nicolas Vergne , Vlad Stefan Barbu

This book is a collective volume authored by leading scientists in the field of stochastic modelling, associated statistical topics and corresponding applications. The main classes of stochastic processes for dependent data investigated throughout this book are Markov, semi-Markov, autoregressive and piecewise deterministic Markov models. The material is divided into three parts corresponding to: (i) Markov and semi-Markov processes, (ii) autoregressive processes and (iii) techniques based on divergence measures and entropies. A special attention is payed to applications in reliability, survival analysis and related fields.

Table contents:

Chapter 1. Variable Length Markov Chains, Persistent Random Walks: A Close Encounter
Chapter 2. Bootstraps of Martingale-difference Arrays Under the Uniformly Integrable Entropy
Chapter 3. A Review of the Dividend Discount Model: From Deterministic to Stochastic Models
Chapter 4. Estimation of Piecewise-deterministic Trajectories in a Quantum Optics Scenario
Chapter 5. Identification of Patterns in a Semi-Markov Chain
Chapter 6. Time Changes and Stationarity Issues for Continuous Time Autoregressive Processes of Order
Chapter 7. Sequential Estimation for Non-parametric Autoregressive Models
Chapter 8. Inference in Parametric and Semi-parametric Models: The Divergence-based Approach
Chapter 9. Dynamics of the Group Entropy Maximization Processes and of the Relative Entropy Group Minimization Processes Based on the Speed-gradient Principle Chapter 10. Inferential Statistics Based on Measures of Information and Divergence
Chapter 11. Goodness-of-Fit Tests Based on Divergence Measures for Frailty Models

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