Probability and statistics

After many years during which it languished in relative obscurity, in remote classrooms of computer science departments and in small prototype projects for tech companies, artificial intelligence (AI) is now a searingly hot topic across the media.

This title was originally published in 1974.

This title was originally published in 1974.

The Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability represents a monumental effort in advancing the discourse on probability theory and statistical applications across a wide range of scientific disciplines.

Harmonic Analysis and the Theory of Probability by Salomon Bochner is a landmark monograph that rigorously links two central domains of modern mathematics: Fourier analysis and probability theory.

The Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability represents a monumental effort in advancing the discourse on probability theory and statistical applications across a wide range of scientific disciplines.

Harmonic Analysis and the Theory of Probability by Salomon Bochner is a landmark monograph that rigorously links two central domains of modern mathematics: Fourier analysis and probability theory.

This title was originally published in 1972.

This title was originally published in 1972.

This title was originally published in 1956.

This title was originally published in 1956.

For every problem, mathematical or otherwise, there is more than one approach and much depends on the ingenuity of the person concerned.

This title was originally published in 1972.

This title was originally published in 1972.

There has been a lot of innovation in systems engineering and some fundamental advances in the fields of optics, imaging, lasers, and photonics that warrant attention.

This book shows the reader how to transform cold numbers into captivating narratives that drive business success.

A Hands-On Way to Learning Data AnalysisPart of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors.

Nonregular factorial designs are a class of factorial designs that enable researchers to study simultaneously the effects of many explanatory variables on a response variable of interest.

This book shows the reader how to transform cold numbers into captivating narratives that drive business success.

This book describes the diverse applications of Gaussian Process (GP) models in mathematical finance.

As the pharmaceutical industry navigates this new era of technological innovation, the integration of AI, big data, and advanced analytics into clinical trials holds immense potential to transform drug development.

This book describes the diverse applications of Gaussian Process (GP) models in mathematical finance.

This book provides a comprehensive overview of discrete mathematics, probability theory, and stochastic processes, covering a wide range of topics in each area.

This book provides a comprehensive overview of discrete mathematics, probability theory, and stochastic processes, covering a wide range of topics in each area.

This Element highlights the archaeology of methods developed in chemometrics, artificial intelligence, and Bayesian statistics.

A bestseller for nearly 25 years, Analysis of Messy Data, Volume 1: Designed Experiments helps applied statisticians and researchers analyze the kinds of data sets encountered in the real world.

The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations.

Parallel processing can be ideally suited for the solving of more complex problems in statistical computing.

Starting from the preliminaries and ending with live examples, Modern Survey Sampling details what a sample can communicate about an unknowable aggregate in a real situation.

This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation.

Quantification of categorical, or non-numerical, data is a problem that scientists face across a wide range of disciplines.

Providing a practical, thorough understanding of how factor analysis works, Foundations of Factor Analysis, Second Edition discusses the assumptions underlying the equations and procedures of this method.

Providing reliable information on an intervention effect, meta-analysis is a powerful statistical tool for analyzing and combining results from individual studies.

Computer simulations based on mathematical models have become ubiquitous across the engineering disciplines and throughout the physical sciences.

The First Book Dedicated to This Class of Longitudinal ModelsAlthough antedependence models are particularly useful for modeling longitudinal data that exhibit serial correlation, few books adequately cover these models.

The US Food and Drug Administration's Report to the Nation in 2004 and 2005 indicated that one of the top reasons for drug recall was that stability data did not support existing expiration dates.

Similar to other data mining and machine learning tasks, multi-label learning suffers from dimensionality.

Analyze Repeated Measures Studies Using Bayesian TechniquesGoing beyond standard non-Bayesian books, Bayesian Methods for Repeated Measures presents the main ideas for the analysis of repeated measures and associated designs from a Bayesian viewpoint.

Explores the Origin of the Recent Banking Crisis and how to Preclude Future CrisesShedding new light on the recent worldwide banking debacle, The Banking Crisis Handbook presents possible remedies as to what should have been done prior, during, and after the crisis.

Asymptotic methods provide important tools for approximating and analysing functions that arise in probability and statistics.

Using time-to-event analysis methodology requires careful definition of the event, censored observation, provision of adequate follow-up, number of events, and independence or "e;noninformativeness"e; of the censoring mechanisms relative to the event.

Based on research projects supported by the National Natural Science Foundation of China and Nanjing University of Aeronautics and Astronautics, Optimization of Regional Industrial Structures and Applications provides an authoritative introduction to and survey of the cutting-edge research and applications in industrial structure optimization.

Enumerative Combinatorics presents elaborate and systematic coverage of the theory of enumeration.