F.F - Probability 1

An award-winning astrophysicist looks at how the understanding of uncertainty and randomness has led to breakthroughs in our knowledge of the cosmos All of us understand the world around us by const……続きを見る

Emerging technologies generate data sets of increased size and complexity that require new or updated statistical inferential methods and scalable, reproducible software. These data sets often invol……続きを見る

Practical in its approach, Applied Bayesian Forecasting and Time Series Analysis provides the theories, methods, and tools necessary for forecasting and the analysis of time series. The authors unif……続きを見る

Set-Indexed Martingales offers a unique, comprehensive development of a general theory of Martingales indexed by a family of sets. The authors establish-for the first time-an appropriate framework t……続きを見る

An Update of the Most Popular Graduate-Level Introductions to Bayesian Statistics for Social ScientistsNow that Bayesian modeling has become standard, MCMC is well understood and trusted, and comput……続きを見る

Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. Whether you work in the eco……続きを見る

This book deals with the development of methodology for the analysis of truncated and censored sample data. It is primarily intended as a handbook for practitioners who need simple and efficient met……続きを見る

Modern Data Visualization with R describes the many ways that raw and summary data can be turned into visualizations that convey meaningful insights. It starts with basic graphs such as bar charts, ……続きを見る

By discussing statistical concepts in the context of transportation planning and operations, Transportation Statistics and Microsimulation provides the necessary background for making informed trans……続きを見る

This text emphasizes nonlinear models for a course in time series analysis. After introducing stochastic processes, Markov chains, Poisson processes, and ARMA models, the authors cover functional au……続きを見る

Learn traditional and cutting-edge machine learning (ML) and deep learning techniques and best practices for time series forecasting, including global forecasting models, conformal prediction, and t……続きを見る

This book explains the primary path to success, using software designed to sample and analyze cashflow and then link that analysis, with forecasting and market research. The case study will start wi……続きを見る

This textbook shall serve a double purpose: first of all, it is a book about generalized stochastic processes, a very important but highly neglected part of probability theory which plays an outstan……続きを見る

Stochastic Differential Equations for Science and Engineering is aimed at students at the M.Sc. and PhD level. The book describes the mathematical construction of stochastic differential equations w……続きを見る

Fundamentals of Mathematical Statistics is meant for a standard one-semester advanced undergraduate or graduate-level course in Mathematical Statistics. It covers all the key topicsーstatistical mod……続きを見る

Create and improve fully automated forecasts for time series data with strong seasonal effects, holidays, and additional regressors using Python Purchase of the print or Kindle book includes a free ……続きを見る

This two-volume text provides a complete overview of the theory of Banach spaces, emphasising its interplay with classical and harmonic analysis (particularly Sidon sets) and probability. The author……続きを見る

This text provides a modern introduction to regression and classification with an emphasis on big data and R. Each chapter is partitioned into a main body section and an extras section. The main bod……続きを見る

A comprehensive and current introduction to the fundamentals of regression analysis Introduction to Linear Regression Analysis, 6th Edition is the most comprehensive, fulsome, and current examinatio……続きを見る

Handbook and reference guide for students and practitioners of statistical regression-based analyses in R Handbook of Regression Analysis with Applications in R, Second Edition is a comprehensive an……続きを見る

This book provides direction in constructing regression routines that can be used with worksheet software on personal computers. The book lists useful references for those readers who desire more in……続きを見る

Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored surviva……続きを見る

Drawing on advanced probability theory, Ambit Stochastics is used to model stochastic processes which depend on both time and space. This monograph, the first on the subject, provides a reference fo……続きを見る

Volume II of this two-volume text and reference work concentrates on the applications of probability theory to statistics, e.g., the art of calculating densities of complicated transformations of ra……続きを見る

This introduction to some of the principal models in the theory of disordered systems leads the reader through the basics, to the very edge of contemporary research, with the minimum of technical fu……続きを見る

Through four previous editions of Advanced Engineering Mathematics with MATLAB, the author presented a wide variety of topics needed by today's engineers. The fifth edition of that book, available n……続きを見る

Volume I of this two-volume text and reference work begins by providing a foundation in measure and integration theory. It then offers a systematic introduction to probability theory, and in particu……続きを見る

This textbook introduces the theory of stochastic processes, that is, randomness which proceeds in time. Using concrete examples like repeated gambling and jumping frogs, it presents fundamental mat……続きを見る

INTRODUCTION TO LINEAR REGRESSION ANALYSIS A comprehensive and current introduction to the fundamentals of regression analysis Introduction to Linear Regression Analysis, 6th Edition is the most com……続きを見る

Research in social and behavioral sciences has benefited from linear regression models (LRMs) for decades to identify and understand the associations among a set of explanatory variables and an outc……続きを見る