Probability and statistics

Quadratic programming is a mathematical technique that allows for the optimization of a quadratic function in several variables.

Action planning has always played a central role in Artificial Intelligence.

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

There are two parts in this book.

An essential guide to two burgeoning topics in machine learning classification trees and ensemble learning Ensemble Classification Methods with Applications in R introduces the concepts and principles of ensemble classifiers methods and includes a review of the most commonly used techniques.

The purpose of this book is to introduce two recent topics in mathematical physics and probability theory: the Schramm-Loewner evolution (SLE) and interacting particle systems related to random matrix theory.

A single source guide to operations research (OR) techniques, this book covers emerging OR methodologies in a clear, concise, and unified manner.

Master GIS Applications on Modelling and Mapping the Risks of DiseasesInfections transmitted by mosquitoes, ticks, triatomine bugs, sandflies, and black flies cause significant rates of death and disease, especially in developing countries.

Presents an up-to-date treatment of the models and methodologies of financial econometrics by one of the world''s leading financial econometricians.

This book is a thorough and self-contained treatise of martingales as a tool in stochastic analysis, stochastic integrals and stochastic differential equations.

This book consists of a series of new, peer-reviewed papers in stochastic processes, analysis, filtering and control, with particular emphasis on mathematical finance, actuarial science and engineering.

This book is a step-by-step data story for analyzing ordinal data from start to finish.

Control theory has applications to a number of areas in engineering and communication theory.

This book presents advanced research on smart health technologies, focusing on the innovative transformations in diagnosis and treatment planning using medical imaging and data analysed by data science techniques.

Praise for the First Edition This book will serve to greatly complement the growing number of texts dealing with mixed models, and I highly recommend including it in one s personal library.

ACM Monograph Series: A Computational Logic focuses on the use of induction in proving theorems, including the use of lemmas and axioms, free variables, equalities, and generalization.

Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed.

Das Buch präsentiert eine anwenderorientierte Darstellung der Verfahren der induktiven Statistik und Datenanalyse.

During the past decade, geneticists have cloned scores of Mendelian disease genes and constructed a rough draft of the entire human genome.

A general class of powerful and flexible modeling techniques, spline smoothing has attracted a great deal of research attention in recent years and has been widely used in many application areas, from medicine to economics.

Climatology and meteorology have basically been a descriptive science until it became possible to use numerical models, but it is crucial to the success of the strategy that the model must be a good representation of the real climate system of the Earth.

Machine Learning: Concepts, Techniques and Applications starts at basic conceptual level of explaining machine learning and goes on to explain the basis of machine learning algorithms.

Originally published in 1984.

The analysis of integrated and co-integrated time series can be considered as the main methodology employed in applied econometrics.

A book in the Systems Evaluation, Prediction, and Decision-Making Series, Systems Evaluation: Methods, Models, and Applications covers the evolutionary course of systems evaluation methods, clearly and concisely.

Studies in bioequivalence are the commonly accepted method to demonstrate therapeutic equivalence between two medicinal products.

Recent Advances in System Reliability discusses developments in modern reliability theory such as signatures, multi-state systems and statistical inference.

"e;This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist.

This book contains 296 exercises and solutions covering a wide variety of topics in linear model theory, including generalized inverses, estimability, best linear unbiased estimation and prediction, ANOVA, confidence intervals, simultaneous confidence intervals, hypothesis testing, and variance component estimation.

Census data is widely used by practitioners to understand demographic change, allocate resources, address inequalities, and make sound business decisions.

This concise volume covers nonparametric statistics topics that most are most likely to be seen and used from a practical decision support perspective.

Differential geometry provides an aesthetically appealing and oftenrevealing view of statistical inference.

This volume is composed of peer-reviewed papers that have developed from the First Conference of the International Society for Non Parametric Statistics (ISNPS).

International Association for Statistical Computing The International Association for Statistical Computing (IASC) is a Section of the International Statistical Institute.

An authoritative, up-to-date graduate textbook on machine learning that highlights its historical context and societal impactsPatterns, Predictions, and Actions introduces graduate students to the essentials of machine learning while offering invaluable perspective on its history and social implications.

This book constitutes the refereed proceedings of the Joint Workshop on Process Algebra and Performance Modeling and Probabilistic Methods in Verification, PAPM-PROBMIV 2001, held in Aachen, Germany in September 2001.

Applied Statistics for the Social and Health Sciences provides graduate students in the social and health sciences with the basic skills that they need to estimate, interpret, present, and publish statistical models using contemporary standards.

Data clustering is a highly interdisciplinary field, the goal of which is to divide a set of objects into homogeneous groups such that objects in the same group are similar and objects in different groups are quite distinct.

This book presents and discusses the numerous measures of test performance that can be derived from 2x2 tables.

This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields.

Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists.

Head hits cause brain damage - but not always.

Americans are bombarded with statistical data each and every day, and healthcare professionals are no exception.

The volume consists entirely of research papers, principally in stochastic calculus, martingales, and Brownian motion, and gathers an important part of the works done in the main probability groups in France (Paris, Strasbourg, Toulouse, Besancon, Grenoble,.

This book constitutes the proceedings of the 17th International Conference on Quantitative Evaluation Systems, QEST 2020, held in Vienna, Austria, in August/September 2020.