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Stochastic Modeling,

Edition 1 A Thorough Guide to Evaluate, Pre-Process, Model and Compare Time Series with MATLAB Software

Editors: By Hossein Bonakdari and Mohammad Zeynoddin

Publication Date: 21 Apr 2022

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Stochastic Modeling: A Thorough Guide to Evaluate, Pre-Process, Model and Compare Time Series with MATLAB Software allows for new avenues in time series analysis and predictive modeling which summarize more than ten years of experience in the application of stochastic models in environmental problems. The book introduces a variety of different topics in time series in the modeling and prediction of complex environmental systems. Most importantly, all codes are user-friendly and readers will be able to use them for their cases. Users who may not be familiar with MATLAB software can also refer to the appendix.

This book also guides the reader step-by-step to learn developed codes for time series modeling, provides required toolboxes, explains concepts, and applies different tools for different types of environmental time series problems.

Key Features

Provides video tutorials on the use of codes
Includes a companion site with 3,000 lines of programming, 70 principal codes and 100 pseudo codes
Highlights multiple methods to Illustrate each problem

About the author

By Hossein Bonakdari, Associate Professor, Dept. of Civil Engineering, Faculty of Engineering, University of Ottawa, Ottawa, Ontario, Canada and Mohammad Zeynoddin, Ph.D. candidate in the field of Soil and Environments, Department of Soils and Agri-Food Engineering, Laval University, Québec, Canada

1. Introduction
2. Preparation and Stationarizing
3. Distribution evaluation and Normalization
4. Stochastic Modeling
5. Goodness-Of-Fit and Precision Criteria
Appendix
MATLAB introduction and basic commands
Introduction
How to execute commands in MATLAB: Frequently used commands
Using MATLAB’s help

ISBN: 9780323917483

Page Count: 366

Retail Price :

9780081027080; 9780128131176; 9780123918864

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Environments, Soil science, Water engineering, hydrology, statistics