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Stochastic Processes
Unlike traditional books presenting stochastic processes in an academic way, this book includes concrete applications that students will find interesting such as gambling, finance, physics, signal processing, statistics, fractals, and biology. Written with an important illustrated guide in the beginning, it contains many illustrations, photos and pictures, along with several website links. Computational tools such as simulation and Monte Carlo methods are included as well as complete toolboxes for both traditional and new computational techniques.
New Developments and Techniques in Structural Equation Modeling
The revision of this edited volume introduces the latest issues and developments in SEM techniques. The book provides an understanding and working knowledge of advanced SEM techniques with a minimum of mathematical derivations. Includes cases & examples.
Recent Developments on Structural Equation Models
After Karl Jöreskog's first presentation in 1970, Structural Equation Modelling or SEM has become a main statistical tool in many fields of science. It is the standard approach of factor analytic and causal modelling in such diverse fields as sociology, education, psychology, economics, management and medical sciences. In addition to an extension of its application area, Structural Equation Modelling also features a continual renewal and extension of its theoretical background. The sixteen contributions to this book, written by experts from many countries, present important new developments and interesting applications in Structural Equation Modelling. The book addresses methodologists and ...
Signed path dependence in financial markets
In Signed path dependence in financial markets: Applications and implications, computer scientist and academic Fabio Dias delves into cutting-edge techniques at the intersection of machine learning, time series analysis, and finance. This comprehensive guide bridges theory and application, offering readers insights into predictive modeling, algorithmic trading, and the nuanced dynamics of option pricing. Dias combines rigorous econometric methods with hands-on machine learning approaches, presenting a toolkit for anyone looking to leverage data-driven insights to navigate and predict complex financial markets. An essential read for practitioners, researchers, and students of financial engineering and quantitative finance.
An Introduction to Applied Multivariate Analysis
This comprehensive text introduces readers to the most commonly used multivariate techniques at an introductory, non-technical level. By focusing on the fundamentals, readers are better prepared for more advanced applied pursuits, particularly on topics that are most critical to the behavioral, social, and educational sciences. Analogies betwe
