This book analyzes the origins of statistical thinking as well as its related philosophical questions, such as causality, determinism or chance. Bayesian and frequentist approaches are subjected to a historical, cognitive and epistemological analysis, making it possible to not only compare the two competing theories, but to also find a potential solution. The work pursues a naturalistic approach, proceeding from the existence of numerosity in natural environments to the existence of contemporary formulas and methodologies to heuristic pragmatism, a concept introduced in the book's final...
This book analyzes the origins of statistical thinking as well as its related philosophical questions, such as causality, determinism or chance. Ba...
This book features a detailed discussion of a strengthened form of the second Borel-Cantelli Lemma and the conditional form of the Borel-Cantelli Lemmas due to Levy, Chen and Serfling. All results are well illustrated by means of many interesting examples.
This book features a detailed discussion of a strengthened form of the second Borel-Cantelli Lemma and the conditional form of the Borel-Cantelli Lemm...
Through real-world datasets, this book shows the reader how to work with material in biostatistics using the open source software R. These include tools that are critical to dealing with missing data, which is a pressing scientific issue for those engaged in biostatistics. Readers will be equipped to run analyses and make graphical presentations based on the sample dataset and their own data. The hands-on approach will benefit students and ensure the accessibility of this book for readers with a basic understanding of R.
Topics include: an introduction to Biostatistics and R, data...
Through real-world datasets, this book shows the reader how to work with material in biostatistics using the open source software R. These include ...
In statistics, the Kalman filter is a mathematical method whose purpose is to use a series of measurements observed over time, containing random variations and other inaccuracies, and produce estimates that tend to be closer to the true unknown values than those that would be based on a single measurement alone. This Brief offers developments on Kalman filtering subject to general linear constraints. There are essentially three types of contributions: new proofs for results already established; new results within the subject; and...
In statistics, the Kalman filter is a mathematical method whose purpose is to use a se...
The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have led to an increased occurrence of industrial processes that utilize statistical process control and capability analysis. These analyses are performed almost exclusively with multivariate methodologies. The aim of this Brief is to present the most important MSQC techniques developed in R language. The book is divided into two parts. The first part contains the basic R elements, an introduction to statistical procedures, and the main aspects...
The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have l...
This is an unusual book because it contains a great deal of formulas. Hence it is a blend of monograph, textbook, and handbook.It is intended for students and researchers who need quick access to useful formulas appearing in the linear regression model and related matrix theory. This is not a regular textbook - this is supporting material for courses given in linear statistical models. Such courses are extremely common at universities with quantitative statistical analysis programs.
This is an unusual book because it contains a great deal of formulas. Hence it is a blend of monograph, textbook, and handbook.It is intended f...
This book aims to provide an overview of some adaptive techniques used in estimating parameters for finite populations where the sampling at any stage depends on the sampling information obtained to date. The sample adapts to new information as it comes in. These methods are especially used for sparse and clustered populations. Written by two acknowledged experts in the field of adaptive sampling.
This book aims to provide an overview of some adaptive techniques used in estimating parameters for finite populations where the sampling at any stage...
This book summarizes results of longstanding research and scientific contributions from many projects and relevant working groups. It collects and evaluates wind and wave climate projections under changing climate having design needs and marine safety in focus. Potential impact of projected climate change in met-ocean conditions on ships and offshore structures is discussed and illustrated by an example of the expected wave climate change on tanker design.
Themonograph is intended for students, researchers and industry based engineers who want a summary of the many studies that...
This book summarizes results of longstanding research and scientific contributions from many projects and relevant working groups. It collects and ...
Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems is a quick primer on the topic that introduces readers to the basic complexities and nuances associated with learning Bayes' theory and inverse probability for the first time. This brief is meant for non-statisticians who are unfamiliar with Bayes' theorem, walkingthem through the theoretical phases of set and sample set selection, the axioms of probability, probability theory as it pertains to Bayes' theorem, and posterior probabilities. All of these concepts are explained as they appear in...
Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems is a quick primer on the topic that introduces ...
Statistical shape analysis is a geometrical analysis from a set of shapes in which statistics are measured to describe geometrical properties from similar shapes or different groups, for instance, the difference between male and female Gorilla skull shapes, normal and pathological bone shapes, etc. Some of the important aspects of shape analysis are to obtain a measure of distance between shapes, to estimate average shapes from a (possibly random) sample and to estimate shape variability in a sample 1]. One of the main methods used is principal component analysis. Specific applications of...
Statistical shape analysis is a geometrical analysis from a set of shapes in which statistics are measured to describe geometrical properties from sim...
