This monograph explores a set of statistical and machine learning tools that can be effectively utilized for applied data analysis in the context of electricity load forecasting.
These are"e; notes based on courses in Theoretical Population Genetics given at the University of Texas at Houston during the winter quarter, 1974, and at the University of Wisconsin during the fall semester, 1976.
This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation.
This book offers a relatively self-contained presentation of the fundamental results in categorical data analysis, which plays a central role among the statistical techniques applied in the social, political and behavioral sciences, as well as in marketing and medical and biological research.
Mendelian Randomization: Methods For Causal Inference Using Genetic Variants provides thorough coverage of the methods and practical elements of Mendelian randomization analysis.
This proceedings volume compiles selected, revised papers presented at the 53rd SouthEastern International Conference on Combinatorics, Graph Theory, and Computing (SEICCGTC 2022), which took place at Florida Atlantic University in Boca Raton, USA, from March 7th to 11th, 2022.
The goal of this book is to put an array of tools at the fingertips of students, practitioners, and researchers by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed.
Probability and Statistics for Physical Sciences, Second Edition is an accessible guide to commonly used concepts and methods in statistical analysis used in the physical sciences.
Focusing on group sequential procedures, summarizes the sequential statistical methods used in anticancer, antiviral, cardiovascular, and gastrointestinal drug research and screening.
Many results, both from semi group theory itself and from the applied sciences, are phrased in discipline-specific languages and hence are hardly known to a broader community.
This book provides an understanding of the concept of marketing and its role in business and public organization including the need for scientific marketing analysis.
Data Science for Sensory and Consumer Scientists is a comprehensive textbook that provides a practical guide to using data science in the field of sensory and consumer science through real-world applications.
This book constitutes the proceedings of the 4th International Workshop on Foundational and Practical Aspects of Resource Analysis, FOPARA 2015, held in London, UK, in April 2015.
The idea of writing up a book on the hydrodynamic behavior of interacting particle systems was born after a series of lectures Claude Kipnis gave at the University of Paris 7 in the spring of 1988.
This book constitutes revised selected papers of the 20th International Conference on Information Technologies and Mathematical Modelling, ITMM 2021, named after A.
The mathematical theory of probability has its roots in attempts to analyse games of chance by Gerolamo Cardano in the sixteenth century, and by Pierre de Fermat and Blaise Pascal in the seventeenth century (for example the ';problem of points').
This richly illustrated book presents the latest techniques for the identifiability analysis and standard and robust regression analysis of complex dynamical models, and looks at their objectives.
This rigorous textbook introduces graduate students to the principles of econometrics and statistics with a focus on methods and applications in financial research.
Economic Time Series: Modeling and Seasonality is a focused resource on analysis of economic time series as pertains to modeling and seasonality, presenting cutting-edge research that would otherwise be scattered throughout diverse peer-reviewed journals.
Bayesian statistical methods have become widely used for data analysis and modelling in recent years, and the BUGS software has become the most popular software for Bayesian analysis worldwide.
This book is concerned with important problems of robust (stable) statistical pat- tern recognition when hypothetical model assumptions about experimental data are violated (disturbed).
