Probability and statistics

This volume of selected and peer-reviewed contributions on the latest developments in time series analysis and forecasting updates the reader on topics such as analysis of irregularly sampled time series, multi-scale analysis of univariate and multivariate time series, linear and non-linear time series models, advanced time series forecasting methods, applications in time series analysis and forecasting, advanced methods and online learning in time series and high-dimensional and complex/big data time series.

As an introduction to Python, this book allows readers to take a slow and steady approach to understanding Python code, explaining concepts, connecting programming with real-life examples, writing Python programs, and completing case studies.

This book introduces the concept of "e;bespoke learning"e;, a new mechanistic approach that makes it possible to generate values of an output variable at each designated value of an associated input variable.

The goal of this unique text is to provide an "e;experience"e; that would facilitate a better transition for mathematics majors to the advanced proof-based courses required for their major.

This book constitutes the refereed proceedings of the 6th International Workshop on Biomedical Image Registration, WBIR 2014, held in London, UK, in July 2014.

Stochastik ist die Mathematik des Zufalls.

This book is about building platforms for pandemic prediction.

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

This book presents theoretical modeling and numerical simulations applied to drive several applications towards Industrial Revolution 4.

This book constitutes the proceedings of the 12th International Workshop on Algorithms and Computation, WALCOM 2018, held in Dhaka, Bangladesh, in March 2018.

This book constitutes the Second Diabetic Foot Ulcers Grand Challenge, DFUC 2021, which was held on September 27, 2021, in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021.

Machine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life.

This book is among the first to present the mathematical models most commonly used to solve optimal execution problems and market making problems in finance.

This is a complete guide to statistics and SPSS for social science students.

This revised book provides a thorough explanation of the foundation of robust methods, incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and regression.

Klaus Danzers Chemometrik - Grundlagen und Anwendungen füllt eine Lücke im deutschsprachigen Lehrbuchmarkt.

The Bible's grand narrative about Israel's Exodus from Egypt is central to Biblical religion, Jewish, Christian, and Muslim identity and the formation of the academic disciplines studying the ancient Near East.

This is the second part of our book on continuous statistical distributions.

A concise, elementary introduction to measure and integration theory, requiring few prerequisites as theory is developed quickly and simply.

This title was originally published in 1972.

Bayesian Nonparametrics for Causal Inference and Missing Data provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or conditional distributions and functional relationships, and their interplay with causal inference and missing data.

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 book provides a captivating journey through the realms of classical and quantum systems as it unravels the profound influence that noise may have on their static and dynamic properties.

Myoung-jae Lee reviews the three most popular methods (and their extensions) in applied economics and other social sciences: matching, regression discontinuity, and difference in differences.

Professionals in all areas business; government; the physical, life, and social sciences; engineering; medicine, etc.

Dieser Buchtitel ist Teil des Digitalisierungsprojekts Springer Book Archives mit Publikationen, die seit den Anfängen des Verlags von 1842 erschienen sind.

This book explores visualization and imputation techniques for missing values and presents practical applications using the statistical software R.

This textbook provides the basic concepts of epidemiology while preparing readers with the skills of applying statistical tools in real-life situations.

This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models.

Generating function (GF) is a mathematical technique to concisely represent a known ordered sequence into a simple continuous algebraic function in dummy variable(s).

This book has been written to fIll a substantial gap in the current literature in mathemat- ical education.

This book introduces best practices in longitudinal data analysis at intermediate level, with a minimum number of formulas without sacrificing depths.

Random evolution denotes a class of stochastic processes which evolve according to a rule which varies in time according to jumps.

This study guide is designed for students taking courses in engineering mathematics and mathematical methods in science.

Score your highest in biostatistics Biostatistics is a required course for students of medicine, epidemiology, forestry, agriculture, bioinformatics, and public health.

This book collects contributions written by well-known statisticians and econometricians to acknowledge Leopold Simar's far-reaching scientific impact on Statistics and Econometrics throughout his career.

A New Way of Analyzing Object Data from a Nonparametric ViewpointNonparametric Statistics on Manifolds and Their Applications to Object Data Analysis provides one of the first thorough treatments of the theory and methodology for analyzing data on manifolds.

How SAS Works is a textbook designed to span the gap between the SAS Institute's "e;Introductory Guide"e;, which is a very basic introduction to the SAS system, and the "e;User's Guide"e;, which is a reference tool for those already well versed in SAS.

A Proven, Hands-On Approach for Students without a Strong Statistical FoundationSince the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing work on the statistical interpretations of machine learning algorithms.

This textbook introduces readers to practical statisticalissues by presenting them within the context of real-life economics andbusiness situations.

This book highlights recent advances in natural computing, including biology and its theory, bio-inspired computing, computational aesthetics, computational models and theories, computing with natural media, philosophy of natural computing, and educational technology.

The main intended audience for this book is undergraduate students in pure and applied sciences, especially those in engineering.

Assembling a collection of very prominent researchers in the field, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area.

This monograph aims to offer a concise introduction to optimal transport, quickly transitioning to its applications in statistics and machine learning.

This volume presents some of the research topics discussed at the 2014-2015 Annual Thematic Program Discrete Structures: Analysis and Applications at the Institute of Mathematics and its Applications during the Spring 2015 where geometric analysis, convex geometry and concentration phenomena were the focus.