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Statistical Topics and Stochastic Models for Dependent Data with Applications
Statistical Topics and Stochastic Models for Dependent Data with Applications
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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 d…
  • Leidėjas:
  • ISBN-10: 1786306034
  • ISBN-13: 9781786306036
  • Formatas: 15.6 x 23.4 x 1.8 cm, kieti viršeliai
  • Kalba: Anglų

Statistical Topics and Stochastic Models for Dependent Data with Applications (el. knyga) (skaityta knyga) | knygos.lt

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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.

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  • Autorius: Vlad Stefan Barbu
  • Leidėjas:
  • ISBN-10: 1786306034
  • ISBN-13: 9781786306036
  • Formatas: 15.6 x 23.4 x 1.8 cm, kieti viršeliai
  • Kalba: Anglų

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.

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