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Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple imputation approach to missing data problems that are often encountered in data analysis.
This book is designed to make spatio-temporal modeling and analysis understandable to students and researchers, mathematicians and statisticians and... Læs mere
Introduction to Python for Science and Engineering offers an incisive introduction to the Python programming language for use in any science or... Læs mere
Maximum Likelihood Estimation with Stata, Fifth Edition is the essential reference and guide for researchers in all disciplines who wish to write... Læs mere
This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch.
This book is an exploration of statistical methodologies and their applications in finance. Readers are taken on a journey in each chapter through... Læs mere
This book presents topics from mathematics which are relevant and useful to computer science. Topics covered include number theory, set theory and functions.... Læs mere
This book offers a systematic and rigorous treatment of continuous-time Markov decision processes, covering both theory and possible applications to queueing systems, epidemiology, finance, and other fields.
This text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning.
This book presents a practical approach to graphic data analysis with real applications front and centre. A knowledge of Statistics is not required, just an interest in data graphics and some experience of working with data.
This uses MATLAB® for data analysis and statistics, offering a broad review of computational data analysis, in particular algebra, trigonometry, regression... Læs mere