Probability and statistics

This book describes the classical axiomatic theories of decision under uncertainty, as well as critiques thereof and alternative theories.

This text presents a wide variety of common types of models found in other mathematical modeling texts, as well as some new types.

In today's fast growing digital world, the web, mobile, social networks and other digital platforms are producing enormous amounts of data that hold intelligence and valuable information.

Biostatistics for Clinical and Public Health Research provides a concise overview of statistical analysis methods.

A firm understanding of the basic statistical methods used in current medical literature is now essential for medical practice, as research papers have become increasingly statistical in nature.

Quantitative Modeling of Derivative Securities demonstrates how to take the basic ideas of arbitrage theory and apply them - in a very concrete way - to the design and analysis of financial products.

This book presents the first part of a planned two-volume series devoted to a systematic exposition of some recent developments in the theory of discrete-time Markov control processes (MCPs).

"e;A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available.

Selected papers submitted by participants of the international Conference "e;Stochastic Analysis and Applied Probability 2010"e; ( www.

This book is for beginners who are struggling to understand and optimize non-linear problems.

A complete and up-to-date discussion of optimal split plot and split block designs Variations on Split Plot and Split Block Experiment Designs provides a comprehensive treatment of the design and analysis of two types of trials that are extremely popular in practice and play an integral part in the screening of applied experimental designs--split plot and split block experiments.

Working in the lab, but unsure what your results actually mean?

Many monitoring, forecasting, and control operations occur in settings where relationships among key measurements must be learned quickly.

This book provides theoretical and applied material for estimating vital parts of demography and health issues including the healthy aging process along with calculating the healthy life years lost to disability.

A Computational Approach to Statistical Learning gives a novel introduction to predictive modeling by focusing on the algorithmic and numeric motivations behind popular statistical methods.

This book is about the choices that researchers can make when building knowledge in social and behavioural spaces.

This book compiles and critically discusses modern engineering system degradation models and their impact on engineering decisions.

Stochastik ist die Mathematik des Zufalls.

This book provides hands-on guidance for researchers and practitioners in criminal justice and criminology to perform statistical analyses and data visualization in the free and open-source software R.

A Second Course in Statistics The past decade has seen a tremendous increase in the use of statistical data analysis and in the availability of both computers and statistical software.

Along with conventional problems of statistics and probability, the - vestigation of problems occurring in what is now referred to as stochastic theory of optimal control also started in the 1940s and 1950s.

Thoroughly updated throughout, A First Course in Linear Model Theory, Second Edition is an intermediate-level statistics text that fills an important gap by presenting the theory of linear statistical models at a level appropriate for senior undergraduate or first-year graduate students.

'Overall, the book is highly technical, including full mathematical proofs of the results stated.

Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others.

This text links the complementary processes of research design and statistical analysis in assessing causal relationships in the social sciences.

Data can be extremely valuable if we are able to extract information from them.

Offering a holistic view of the pioneering trends and innovations in smart healthcare management, this book focuses on the methodologies, frameworks, design issues, tools, architectures, and technologies necessary to develop and understand intelligent healthcare systems and emerging applications in the present era.

This book constitutes the referred proceedings of the 11th International Workshop on Practical Applications of Stochastic Modelling, PASM 2022, was held in Alicante, Spain, in September 2022.

Containing a summary of several recent results on Markov-based input modeling in a coherent notation, this book introduces and compares algorithms for parameter fitting and gives an overview of available software tools in the area.

Our book, Future of Tech Startups and Innovations in the Age of AI, mainly focuses on artificial intelligence (AI) tools, AI-based startups, AI-enabled innovations, Autonomous AI Agents (Auto-GPT), AI-based marketing startups, machine learning for organizations, AI-internet of things (IoT) for new tech companies, AI-enabled drones for agriculture industry, machine learning (ML)/deep learning (DL)-based drip farming, AI-based driverless cars, AI-based weather prediction startups, AI tools for personal branding, AI-based teaching, AI-based doctor/hospital startups, AI for game companies, AI-based finance tools, AI for human resource management, AI-powered management tools, AI tools for future pandemics, AI/ML-based transportation companies, AI for media, AI for carrier counseling, AI for customer care, AI for next generation businesses, and many more applications.

This volume presents a comprehensive compilation of chapters whose topics were presented at the 2nd International Conference on Mathematical Analysis and Application in Modeling (CMAAM-2023), held at the Department of Mathematics & the Center for Mathematical Biology and Ecology, Jadavpur University, Kolkata, West Bengal, India, from 9-11 October 2023.

Das Buch vermittelt moderne Konzepte der Matrix-Algebra, die beispielsweise bei der Lösung linearer Gleichungssysteme und im linearen Regressionsmodell von großem Nutzen sind.

The main new feature of the fifth edition is the addition of a new chapter, Chapter 12, on applications to mathematical finance.

The book gives an up-to-date account of various approaches availablefor the analysis of infectious disease data.

Protein informatics is a newer name for an already existing discipline.

Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered, and unordered categorical response regression procedures.

A Criminologist's Guide to R: Crime by the Numbers introduces the programming language R and covers the necessary skills to conduct quantitative research in criminology.

Need to learn Minitab?

This book belongs to the subject of control and systems theory.

A comprehensive and timely edition on an emerging new trend in time series Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH sets a strong foundation, in terms of distribution theory, for the linear model (regression and ANOVA), univariate time series analysis (ARMAX and GARCH), and some multivariate models associated primarily with modeling financial asset returns (copula-based structures and the discrete mixed normal and Laplace).

Gain the statistics skills you need for the social sciences with this accessible introductory guide Statistical Methods for the Social Sciences, 5th Edition, Global Edition, by Alan Agresti, introduces you to statistical methods used in social science disciplines with no previous knowledge of statistics necessary.

Based on the author's experience in teaching data science for more than 10 years, Mathematics and Programming for Machine Learning with R: From the Ground Up reveals how machine learning algorithms do their magic and explains how these algorithms can be implemented in code.

Models in Statistical Social Research provides a comprehensive insight of models used in statistical social research based on statistical data and methods.

This volume presents a unique collection of original research contributions by leading experts in several modern fields of econometrics and statistics, including high-dimensional, nonparametric and robust statistics, time series analysis and factor models.