Probability and statistics

This book provides the tools, the methods, and the theory to meet the challenges of contemporary data science applied to geographic problems and data.

This book covers the computational aspects of psychometric methods involved in developing measurement instruments and analyzing measurement data in social sciences.

Gather and analyze data successfully, identify trends, and then create overarching strategies and actionable next steps - all through Excel.

An award-winning history of the Enlightenment quest to devise a mathematical model of rationalityWhat did it mean to be reasonable in the Age of Reason?

This book provides state-of-art statistical methodologies, practical considerations from regulators and sponsors, logistics, and real use cases for practitioners for the uptake of RWE/D.

This book provides robust analysis and synthesis tools for Markovian jump systems in the finite-time domain with specified performances.

This book presents a selection of peer-reviewed contributions on the latest developments in time series analysis and forecasting, presented at the 7th International Conference on Time Series and Forecasting, ITISE 2021, held in Gran Canaria, Spain, July 19-21, 2021.

This textbook integrates scientific programming with the use of R and uses it both as a tool for applied problems and to aid in learning calculus ideas.

This book discusses Artificial Neural Networks (ANN) and their ability to predict outcomes using deep and shallow learning principles.

Applied Linear Regression for Business Analytics with R introduces regression analysis to business students using the R programming language with a focus on illustrating and solving real-time, topical problems.

This book provides readers with a comprehensive overview of the latest developments in the field of smart manufacturing, exploring theoretical research, technological advancements, and practical applications of AI approaches.

Climate change, increasing population, food-versus-fuel economics, pandemics, etc.

Climate change, increasing population, food-versus-fuel economics, pandemics, etc.

Für empirische Wirtschaftswissenschaftler gehören ökonometrische Methoden zum Standardwerkzeug.

Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance.

This book introduces the reader to data science using R and the tidyverse.

This book introduces the reader to data science using R and the tidyverse.

Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance.

This book, written in honor of Arno Tausch, presents cutting-edge research on globalization, development, and global values.

Analysis of Categorical Data with R, Second Edition presents a modern account of categorical data analysis using the R software environment.

A Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.

The methodological needs of environmental studies are unique in the breadth of research questions that can be posed, calling for a textbook that covers a broad swath of approaches to conducting research with potentially many different kinds of evidence.

This book describes extensions of Sudakov's classical result on the concentration of measure phenomenon for weighted sums of dependent random variables.

Computational intelligence consists of those techniques that imitate the human brain and nature to adopt the decision-making approach.

This book provides a quick but insightful introduction to Bayesian tracking and particle filtering for a person who has some background in probability and statistics and wishes to learn the basics of single-target tracking.

Despite the critical importance of the cerebellum in brain function, the scientific community still lacks effective treatments for most cerebellar ataxias.

The book offers an introduction to the technical foundation of decentralized insurance models, for advanced undergraduate students, graduate students and practitioners.

Handbook of Statistical Analysis: AI and ML Applications, third edition, is a comprehensive introduction to all stages of data analysis, data preparation, model building, and model evaluation.

Practical Handbook of Curve Fitting is a reference work assembled by Arlinghaus and a set of editors with well over a century of combined experience in various disciplines and activities related to curve fitting.

Finding effective methods for mosquito control remains one of the great global challenges facing this generation.

In an age when electronic health records (EHRs) are an increasingly important source of data, this essential textbook provides both practical and theoretical guidance to researchers conducting epidemiological or clinical analysis through EHRs.

In an age when electronic health records (EHRs) are an increasingly important source of data, this essential textbook provides both practical and theoretical guidance to researchers conducting epidemiological or clinical analysis through EHRs.

Finding effective methods for mosquito control remains one of the great global challenges facing this generation.

Practical Handbook of Curve Fitting is a reference work assembled by Arlinghaus and a set of editors with well over a century of combined experience in various disciplines and activities related to curve fitting.

Modelling Survival Data in Medical Research, Fourth Edition, describes the analysis of survival data, illustrated using a wide range of examples from biomedical research.

How does chance enter our world?

Deep learning is an important element of artificial intelligence, especially in applications such as image classification in which various architectures of neural network, e.

Deep learning is an important element of artificial intelligence, especially in applications such as image classification in which various architectures of neural network, e.

Special functions play a very important role in solving various families of ordinary and partial differential equations as well as their fractional-order analogs, which model real-life situations.

Computational intelligence consists of those techniques that imitate the human brain and nature to adopt the decision-making approach.

This book provides a quick but insightful introduction to Bayesian tracking and particle filtering for a person who has some background in probability and statistics and wishes to learn the basics of single-target tracking.

Despite the critical importance of the cerebellum in brain function, the scientific community still lacks effective treatments for most cerebellar ataxias.

Sample Sizes for Clinical Trials, Second Edition is a practical book that assists researchers in their estimation of the sample size for clinical trials.

Sample Sizes for Clinical Trials, Second Edition is a practical book that assists researchers in their estimation of the sample size for clinical trials.

The Data Preparation Journey: Finding Your Way With R introduces the principles of data preparation within in a systematic approach that follows a typical data science or statistical workflow.

This is the first comprehensive book on Trotter-Kato approximations of stochastic differential equations (SDEs) in infinite dimensions and applications.

This book offers an introduction to applied statistics through data analysis, integrating statistical computing methods.

This text presents the basic theory of random walks on infinite, finitely generated groups, along with certain background material in measure-theoretic probability.

The use of Bayesian statistics has grown significantly in recent years, and will undoubtedly continue to do so.

Everyday we face decisions that carry an element of risk and uncertainty.