Probability and statistics

Linear Algebra and Linear Models comprises a concise and rigorous introduction to linear algebra required for statistics followed by the basic aspects of the theory of linear estimation and hypothesis testing.

This self-contained beginning graduate text covers linear and integer programming, polytopes, matroids and matroid optimization, shortest paths, and network flows.

Every finance professional wants and needs a competitive edge.

This book presents a selection of peer-reviewed contributions to the fourth Bayesian Young Statisticians Meeting, BAYSM 2018, held at the University of Warwick on 2-3 July 2018.

This monograph discusses recent advances in ergodic theory and dynamical systems.

Frontiers in Data Science deals with philosophical and practical results in Data Science.

Traditions of the 150-year-old St.

The use of statistics in biology, medicine, engineering, and the sciences has grown dramatically in recent years and having a basic background in the subject has become a near necessity for students and researchers in these fields.

Interactive Particle Systems is a branch of Probability Theory with close connections to Mathematical Physics and Mathematical Biology.

Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing.

Features an integrated approach of statistical scenarios and simulations to aid readers in developing key intuitions needed to understand the wide ranging concepts and methods of statistics and inference Illuminating Statistical Analysis Using Scenarios and Simulations presents the basic concepts of statistics and statistical inference using the dual mechanisms of scenarios and simulations.

Early approaches to accelerated testing were based on the assumption that there was a simple acceleration factor that would correspond to a linear scaling of time from the operating stress to the accelerating stress.

Data Analysis, Data Handling and Business Intelligence are research areas at the intersection of computer science, artificial intelligence, mathematics, and statistics.

This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it.

Quantitative Methods in Transportation provides the most useful, simple, and advanced quantitative techniques for solving real-life transportation engineering problems.

Statistical concepts provide scientific framework in experimental studies, including randomized controlled trials.

This book is the outcome of the CIMPA School on Statistical Methods and Applications in Insurance and Finance, held in Marrakech and Kelaat M'gouna (Morocco) in April 2013.

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.

Generate and Analyze Multi-Level Data Spatial microsimulation involves the generation, analysis, and modeling of individual-level data allocated to geographical zones.

A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Few books on statistical data analysis in the natural sciences are written at a level that a non-statistician will easily understand.

Nonparametric Regression and Generalized Linear Models focuses on the roughness penalty method of nonparametric smoothing and shows how this technique provides a unifying approach to a wide range of smoothing problems.

Provides graduate students in the social sciences with the basic skills they need to estimate, interpret, present, and publish basic regression models using contemporary standards.

This book constitutes the refereed proceedings of the 15th International Conference on Simulation of Adaptive Behavior, SAB 2018, held in Frankfurt/Main, Germany, in August 2018.

This book is for those interested in number systems, abstract algebra, and analysis.

Highly recommended by JASA, Technometrics, and other leading statistical journals, the first two editions of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs.

Matrix-analytic and related methods have become recognized as an important and fundamental approach for the mathematical analysis of general classes of complex stochastic models.

This engaging book helps readers identify and then discard 52 misconceptions about data and statistical summaries.

Das vorliegende Buch basiert im wesentlichen auf dem Studienkurs "Umfrageforschung und Sekundäranalyse von Umfragedaten (am Beispiel des ALLBUS)" (Dreifachkurseinheit 3606), den ich für die FernUniversität/Gesamthochschule in Hagen verfasst habe.

This second BiBoS volume surveys recent developments in the theory of stochastic processes.

This book examines information processing performed by bio-systems at all scales: from genomes, cells and proteins to cognitive and even social systems.

This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software.

Permutation tests permit us to choose the test statistic best suited to the task at hand.

In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics.

Data Scientists are experts at analyzing, modelling and visualizing data but, at one point or another, have all encountered difficulties in collaborating with or delivering their work to the people and systems that matter.

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

Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc.

This book introduces the latest research on advanced control charts and new machine learning approaches to detect abnormalities in the smart manufacturing process.

Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems.

This book examines biomass mixture modeling and optimization.

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

This volume contains papers which were presented at the XV Latin American Congress of Probability and Mathematical Statistics (CLAPEM) in December 2019 in Merida-Yucatan, Mexico.

This book describes many types of Conference matrices and shows the case studies of application.

Since 1945, "e;The Annual Deming Conference on Applied Statistics"e; has been an important event in the statistics profession.

This book provides a comprehensive survey of the most recent methodology--both theoretical and applied--on the statistical analysis and detection of defective/"e;non-conforming"e; items in various types of inspection for attributes, when the inspection itself is subject to error.