Probability and statistics

This book contains three lectures each of 10 sessions; the first on Potential Theory on graphs and manifolds, the second on annealing and another algorithms for image reconstruction, the third on Malliavin Calculus.

Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to-date reference works are available.

With the rapidly advancing fields of Data Analytics and Computational Statistics, it's important to keep up with current trends, methodologies, and applications.

In the view of many probabilists, author Anatolii Puhalskii's research results stand among the most significant achievements in the modern theory of large deviations.

This book discusses chemometric methods for spectroscopy analysis including NIR, MIR, Raman, NMR, and LIBS, from the perspective of practical applied spectroscopy.

Basic Statistics and Epidemiology is a straightforward primer in basic statistics that emphasizes its practical use in epidemiology and public health, providing an understanding of essential topics such as study design, data analysis and statistical methods used in the execution of medical research.

The book focuses on several skew-normal mixed effects models, and systematically explores statistical inference theories, methods, and applications of parameters of interest.

Focusing on p-adic and adelic analogues of pseudodifferential equations, this monograph presents a very general theory of parabolic-type equations and their Markov processes motivated by their connection with models of complex hierarchic systems.

If you know how to program, you have the skills to turn data into knowledge.

This BASS book Series publishes selected high-quality papers reflecting recent advances in the design and biostatistical analysis of biopharmaceutical experiments - particularly biopharmaceutical clinical trials.

This handbook provides full coverage of the most recent and advanced topics in scheduling, assembling researchers from all relevant disciplines to facilitate new insights.

Dynamic Time Series Models using R-INLA: An Applied Perspective is the outcome of a joint effort to systematically describe the use of R-INLA for analysing time series and showcasing the code and description by several examples.

The Birnbaum-Saunders Distribution presents the statistical theory, methodology, and applications of the Birnbaum-Saunders distribution, a very flexible distribution for modeling different types of data (mainly lifetime data).

This textbook provides an introduction to financial option valuation for undergraduates.

An overview of the asymptotic theory of optimal nonparametric tests is presented in this book.

The study of random sets is a large and rapidly growing area with connections to many areas of mathematics and applications in widely varying disciplines, from economics and decision theory to biostatistics and image analysis.

Finance and insurance companies are facing a wide range of parametric statistical problems.

Praise for the Second Edition "e;A must-have book for anyone expecting to do research and/or applications in categorical data analysis.

This book features original research articles on the topic of mathematical modelling and fractional differential equations.

This textbook grew out of notes for the ECE143 Programming for Data Analysis class that the author has been teaching at University of California, San Diego, which is a requirement for both graduate and undergraduate degrees in Machine Learning and Data Science.

Readers who want a less mathematical alternative to the EQS manual will find exactly what they're looking for in this practical text.

Fully updated to reflect the 2022 ASQ Certified Six Sigma Black Belt (CSSBB) Body of Knowledge (BoK), The ASQ Certified Six Sigma Black Belt Handbook, Fourth Edition is ideal for candidates studying for the CSSBB examination.

In the era of Big Data our society is given the unique opportunity to understand the inner dynamics and behavior of complex socio-economic systems.

Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade.

Outside of randomized experiments, association does not imply causation, and yet there is nothing defective about our knowledge that smoking causes lung cancer, a conclusion reached in the absence of randomized experimentation with humans.

This book introduces optimal control problems for large families of deterministic and stochastic systems with discrete or continuous time parameter.

This book presents the fundamentals of stochastic thermodynamics, one of the most central subjects in non-equilibrium statistical mechanics.

All models are lies.

Making Sense of Statistics, Eighth Edition, is the ideal introduction to the concepts of descriptive and inferential statistics for students undertaking their first research project.

Econophysics explores the parallels between physics and economics and is an exciting topic that is attracting increasing attention.

This classic textbook is suitable for a first course in the theory of statistics for students with a background in calculus, multivariate calculus, and the elements of matrix algebra.

Intermediate Probability is the natural extension of the author's Fundamental Probability.

Fundamental Concepts for New Clinical Trialists describes the core scientific concepts of designing, data monitoring, analyzing, and reporting clinical trials as well as the practical aspects of trials not typically discussed in statistical methodology textbooks.

Statistical Concepts-A First Course presents the first 10 chapters from An Introduction to Statistical Concepts, Fourth Edition.

This book is the first of a series which focuses on the interpolation and extrapolation of optimal designs, an area with significant applications in engineering, physics, chemistry and most experimental fields.

Graph Searching Games and Probabilistic Methods is the first book that focuses on the intersection of graph searching games and probabilistic methods.

Mechanizing hypothesis formation is an approach to exploratory data analysis.

This book is useful not only for young but also for mature scientists who are preparing methods for studying natural environmental phenomena and their alteration by human activity.

This extraordinary compilation is an expansion of the recent American Mathematical Society Special Session celebrating M.

A Cohesive Approach to Regression ModelsConfidence Intervals in Generalized Regression Models introduces a unified representation-the generalized regression model (GRM)-of various types of regression models.

This book presents the theory of rational decisions involving the selection of stopping times in observed discrete-time stochastic processes, both by single and multiple decision-makers.

Just Enough R!

This first volume includes papers presented at the Eleventh World Congress of the Econometric Society, addressing topics such as dynamic mechanism design, agency problems, and networks.

This book applies the multidisciplinary approaches of econometrics, statistics, finance and artificial intelligence for pricing and forecasting the carbon market in the context of managerial issues.

Biosimulation is an approach to biomedical research and the treatment of patients in which computer modeling goes hand in hand with experimental and clinical work.

An observational study is an empiric investigation of the effects caused by a treatment, policy, or intervention in which it is not possible to assign subjects at random to treatment or control, as would be done in a controlled experiment.