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Change-Point Analysis in Nonstationary Stochastic Models

in change-point analysis and stochastic modelling, the book includes theoretical details combined with computer simulations and practical;

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Change-Point Analysis in Nonstationary Stochastic Models

in change-point analysis and stochastic modelling, the book includes theoretical details combined with computer simulations and practical;

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Stochastic Models, Statistics and Their Applications

contributions focus on statistical inference, quality control, change-point analysis and detection, empirical processes, time series analysis, survival;

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Themes in Modern Econometrics

nonstationary seasonal stochastic processes. They also cover the latest contributions to the theory and practice of seasonal adjustment, together with;

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The Econometric Analysis of Seasonal Time Series

nonstationary seasonal stochastic processes. They also cover the latest contributions to the theory and practice of seasonal adjustment, together with;

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Time Series Analysis

discuss nonstationary panel data analysis, the problem of differentiating between deterministic and stochastic trends, and nonstationary processes;

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Stochastic Calculus and Differential Equations for Physics and Finance

stochastic processes, using those methods in a unified way. The focus is on nonstationary processes, and statistical ensembles are emphasized in time;

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Stochastic Geometry for Image Analysis

This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process;

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Point Processes

This book describes the properties of stochastic probabilistic models and develops the applied mathematics of stochastic point processes;

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Hilbert And Banach Space-valued Stochastic Processes

of infinite-dimensional stationary and nonstationary stochastic processes or time series, based on Hilbert and Banach space-valued second order random;

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Simulation and Inference for Stochastic Processes with Yuima: A Comprehensive R Framework for Sdes and Other Stochastic Processes

point analysis, hypotheses testing, asynchronous covariance estimation, lead-lag estimation, LASSO model selection, and so on. YUIMA also;

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Stochastic Biomathematical Models

systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and;

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Bayesian Analysis of Stochastic Process Models

Bayesian analysis of complex models based on stochastic processes has in recent years become a growing area. This book provides a unified;

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Analytically Tractable Stochastic Stock Price Models

Asymptotic analysis of stochastic stock price models is the central topic of the present volume. Special examples of such models are;

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Nonstationary Panels, Panel Cointegration, and Dynamic Panels

correlation common features analysis to nonstationary panel data models; study the local power of panel unit root test statistics; derive the;

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Learning Automata

number of choices responds in a random environment. Topics include fixed structure automata, variable structure stochastic automata, convergence;

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Handbook of Stochastic Models and Analysis of Manufacturing System Operations

This handbook surveys important stochastic problems and models in manufacturing system operations and their stochastic analysis. Using;

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Point Process Calculus in Time and Space

) point processes.The applications covered in this text (queueing, information theory, stochastic geometry and signal analysis) have been chosen;

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Option Pricing and Estimation of Financial Models with R

covariation estimation, change point analysis, asymptotic expansion and classification of financial time series from a statistical viewpoint. The book;

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Missing Data Methods

, covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian;

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Missing Data Methods

, covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian;

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A Practitioner's Guide to Stochastic Frontier Analysis Using Stata

A Practitioner's Guide to Stochastic Frontier Analysis Using Stata provides practitioners in academia and industry with a step-by-step;

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A Practitioner's Guide to Stochastic Frontier Analysis Using Stata

A Practitioner's Guide to Stochastic Frontier Analysis Using Stata provides practitioners in academia and industry with a step-by-step;

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Stochastic Model Checking

The use of stochastic models in computer science is wide spread, for instance in performance modeling, analysis of randomized algorithms;

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Applied Stochastic Hydrogeology

. The first part of the book discusses fully stochastic distributed methodology for flood frequency analysis and an analysis of the occurrence;

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Stochastic Modelling Of Aids Epidemiology And Hiv Pathogenesis

analysis of deterministic and statistical models in the literature; (3) it develops state space models by combining stochastic models and;

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Stochastic Modelling of Reactionâ Diffusion Processes

reactions, introducing stochastic simulation algorithms and mathematical methods for analysis of stochastic models. Different stochastic spatio;

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