Probability and statistics

Sparse models are particularly useful in scientific applications, such as biomarker discovery in genetic or neuroimaging data, where the interpretability of a predictive model is essential.

This 1971 classic on linear models is once again available--as a Wiley Classics Library Edition.

The purpose of this book is to provide the reader with a solid background and understanding of the basic results and methods in probability the- ory before entering into more advanced courses (in probability and/or statistics).

Presents the state of the art in sparse and multiscale image and signal processing.

A one-of-a-kind resource on identifying and dealing with bias in statistical research on causal effects Do cell phones cause cancer?

There exists a large variety of image reconstruction methods proposed by different authors (see e.

Statistics covers the basic principles of Statistics.

The book presents selected papers from NIELIT's International Conference on Communication, Electronics and Digital Technology (NICEDT-2024) held during 16-17 February 2024 in Guwahati, India.

Probability and Statistical Inference: From Basic Principles to Advanced Models covers aspects of probability, distribution theory, and inference that are fundamental to a proper understanding of data analysis and statistical modelling.

Recognized as a "e;Recommended"e; title by Choice for their April 2021 issue.

South and Southeast Asian countries are experiencing rapid land cover and land use changes (LCLUC) driven by urbanization, agricultural expansion, deforestation, and infrastructure development.

Part one of a comprehensive text on multidimensional real analysis, including numerous exercises with partial solutions.

Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle.

A thorough review of the most current regression methods in time series analysis Regression methods have been an integral part of time series analysis for over a century.

Highly praised for its broad, practical coverage, the second edition of this popular text incorporated the major statistical models and issues relevant to epidemiological studies.

Leading authorities cover a wide range of currently topical problems in probability and mathematical genetics.

Tackling the question of how to effectively aggregate uncertain preference information in multiple structures given by decision-making groups, Theory and Approaches of Unascertained Group Decision-Making focuses on group aggregation methods based on uncertainty preference information.

This book discusses recent developments in dynamic reliability in multi-state systems (MSS), addressing such important issues as reliability and availability analysis of aging MSS, the impact of initial conditions on MSS reliability and availability, changing importance of components over time in MSS with aging components, and the determination of age-replacement policies.

It was written on another occasion* that "e;It is apparent that the scientific culture, if one means production of scientific papers, is growing exponentially, and chaotically, in almost every field of investigation"e;.

This book is an introduction to social data analytics along with its challenges and opportunities in the age of Big Data and Artificial Intelligence.

A significant step forward in the world of earth observation was made with the development of imaging spectrometry.

Why study the theory of experiment design?

Probability has fascinated philosophers, scientists, and mathematicians for hundreds of years.

A one-stop introduction to the methods of ergodic theory applied to holomorphic iteration that is ideal for graduate courses.

As computers proliferate and as the field of computer graphics matures, it has become increasingly important for computer scientists to understand how users perceive and interpret computer graphics.

This  comprehensive book, rich with applications,  offers a quantitative framework for the analysis of the various capture-recapture models for open animal populations, while also addressing associated computational methods.

Comparative effectiveness research (CER) is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or to improve the delivery of care (IOM 2009).

This book provides straightforward conceptual explanations of statistical methods for the life sciences, specially designed for students lacking a strong mathematical background.

This book offers a modern and accessible introduction to Statistical Inference, the science of inferring key information from data.

This book offers an easily accessible and comprehensive guide to the entire market research process, from asking market research questions to collecting and analyzing data by means of quantitative methods.

This title was originally published in 1972.

There are many books written about statistics, some brief, some detailed, some humorous, some colorful, and some quite dry.

This accessible new edition explores the major topics in Monte Carlo simulation that have arisen over the past 30 years and presents a sound foundation for problem solving Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the state-of-the-art theory, methods and applications that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago.

A core task in statistical analysis, especially in the era of Big Data, is the fitting of flexible, high-dimensional, and non-linear models to noisy data in order to capture meaningful patterns.

Emerging technologies generate data sets of increased size and complexity that require new or updated statistical inferential methods and scalable, reproducible software.

Incorporating a collection of recent results, Polya Urn Models deals with discrete probability through the modern and evolving urn theory and its numerous applications.

The Hinfinity control has been one of the important robust control approaches since the 1980s.

Synergetic Economics presents a new advance in analytical economics.

Demonstrates how nonresponse in sample surveys and censuses can be handled by replacing each missing value with two or more multiple imputations.

A comprehensive look at how probability and statistics is applied to the investment process Finance has become increasingly more quantitative, drawing on techniques in probability and statistics that many finance practitioners have not had exposure to before.

This book covers major measure theory topics with a fairly extensive study of their applications to probability and analysis.

In today's manufacturing environment, managing inventories is one of the basic concerns of enterprises dealing with materials according to their activities.

This is an introductory-level text on stochastic modeling.

Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers.

Interactively Run Simulations and Experiment with Real or Simulated Data to Make Sequential Analysis Come AliveTaking an accessible, nonmathematical approach to this field, Sequential Methods and Their Applications illustrates the efficiency of sequential methodologies when dealing with contemporary statistical challenges in many areas.

This book of peer-reviewed short papers on methodological and applied statistics and demography is the fourth of four volumes from the 52nd Scientific Meeting of the Italian Statistical Society (SIS 2024), held in Bari, Italy, on June 17-20, 2024.

Helping you become a creative, logical thinker and skillful "e;simulator,"e; Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms, and Case Studies provides broad coverage of the entire drug development process, from drug discovery to preclinical and clinical trial aspects to commercialization.