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Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction... Read More >>
Practical Time Series Analysis for Data Science is an accessible guide that doesn’t require a background in calculus... Read More >>
Like the De Groot winning first edition, the second edition of Principles of Uncertainty is an accessible, comprehensive... Read More >>
"The bestselling author of Sprawlball, Kirk Goldsberry returns with a visual feast of a book--equal parts Book of... Read More >>
Currently, there are a lack of intermediate /advanced level textbooks which introduce students and practicing statisticians... Read More >>
This book provides a compact exposition of the results explaining interrelations between diffusion stochastic processes,... Read More >>
The purpose of applying mathematical theory to the theory of statistical inference is to make it simpler and more... Read More >>
This book investigates statistical observables for anomalous and nonergodic dynamics, focusing on the dynamical... Read More >>
Stochastic Processes with R: An Introduction cuts through the heavy theory that is present in most courses on random... Read More >>
Thoroughly updated throughout, this second edition will continue to be about the practicable methods of statistical... Read More >>
By deploying time series analysis, Fourier transform, functional analysis, min-plus convolution, and fractional... Read More >>
Object Oriented Data Analysis (OODA) provides a useful general framework for the consideration of many types of... Read More >>
This book investigates the world of leading indicators and explores how they can effectively be used, providing... Read More >>
This one- or two-term calculus-based basic probability text is written for majors in mathematics, physical sciences,... Read More >>
