This venture aspires to be a mix of a textbook at the undergraduate and postgraduate levels and a monograph to catch the attention of researchers in theoretical and practical aspects of survey sampling at diverse levels demanding a comprehensive review of what useful materials have preceded, with an eye to what beacons to the depth of the imminent future.
This easy-to-follow applied book on semiparametric regression methods using R is intended to close the gap between the available methodology and its use in practice.
With increasing rates of pollution to both land and aquatic environments, regulations for the quality of our waters are necessarily becoming more stringent.
This book hosts the results presented at the 6th Bayesian Young Statisticians Meeting 2022 in Montreal, Canada, held on June 22-23, titled "e;Bayesian Statistics, New Generations New Approaches"e;.
Against the background of AIDS, wars, migration, and the inadequate provision of health care, a very serious epidemic of tuberculosis is once again occurring worldwide.
Advances in the biomedical sciences, especially genomics, proteomics, and metabolomics, taken together with the expanding use of electronic health records, are radically changing the IT infrastructure and software applications needed to support the transfer of knowledge from bench to bedside.
Beginning with familiar models and moving onto advanced semiparametric modelling tools Semiparametric Odds Ratio Model and its Applications introduces readers to a new range of flexible statistical models and provides guidance on their application using real data examples.
Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition of the methods of statistical inference for students who are comfortable with mathematical notation.
This book describes the integration of high-throughput bioinformatics data from multiple platforms to inform our understanding of the functional consequences of genomic alterations.
Data Gathering, Analysis and Protection of Privacy through Randomized Response Techniques: Qualitative and Quantitative Human Traits tackles how to gather and analyze data relating to stigmatizing human traits.
This book presents data-driven algorithms used in the context of wind farm modelling and exploits their relation with concepts from non-linear dynamical system theory.
SAS for Elementary Statistics: Getting Started provides an introduction to SAS programming for those who have experience with introductory statistical methods.
Learn statistical methods quickly and easily with the discovery method With its emphasis on the discovery method, this publication encourages readers to discover solutions on their own rather than simply copy answers or apply a formula by rote.
In this book, the optimal transportation problem (OT) is described as a variational problem for absolutely continuous stochastic processes with fixed initial and terminal distributions.
Wavelets from a Statistical Perspective offers a modern, 2nd generation look on wavelets, far beyond the rigid setting of the equispaced, dyadic wavelets in the early days.
Although valued for its ability to allow teams to collaborate and foster coalitional behaviors among the participants, game theory's application to networking systems is not without challenges.
This book is the first in the literature to present the state of the art and some interesting and relevant applications of the Fuzzy Analytic Hierarchy Process (FAHP).
This book provides a novel perspective on human migration dynamics by examining it through the lenses of complex systems science and philosophy of science.
Up-to-Date Research Sheds New Light on This Area Taking into account the ongoing worldwide financial crisis, Stock Market Volatility provides insight to better understand volatility in various stock markets.
This book is intended for undergraduate students of Mathematics, Statistics, and Physics who know nothing about Monte Carlo Methods but wish to know how they work.
Bringing together relevant statistical and probabilistic techniques, a practical manual for advanced undergraduate and graduate students and professional astronomers.
This interdisciplinary reference and guide provides an introduction to modeling methodologies and models which form the starting point for deriving efficient and effective solution techniques, and presents a series of case studies that demonstrate how heuristic and analytical approaches may be used to solve large and complex problems.
With the boom of big data and machine learning and the subsequent need for parallel processing technologies, fork-join queues are more relevant now than ever before.
Guillaume Wunsch, Michel Mouchart, Josianne Duchene This book is an outcome of the activities of the Working Group on Health, Morbidity, and Mortality Differentials of the European Association for Population Studies, which was chaired for some years by one of the present editors (G.
In multivariate data analysis, regression techniques predict one set of variables from another while principal component analysis (PCA) finds a subspace of minimal dimensionality that captures the largest variability in the data.
This book provides an introduction to the theory of linear systems and control for students in business mathematics, econometrics, computer science, and engineering.
Since the first edition of this book was published, S-PLUS has evolved markedly with new methods of analysis, new graphical procedures, and a convenient graphical user interface (GUI).
A comprehensive overview of data science covering the analytics, programming, and business skills necessary to master the discipline Finding a good data scientist has been likened to hunting for a unicorn: the required combination of technical skills is simply very hard to find in one person.
