Although data engineering is a multi-disciplinary field with applications in control, decision theory, and the emerging hot area of bioinformatics, there are no books on the market that make the subject accessible to non-experts.
A one-stop reference to the major techniques for analyzing microwave planar transmission line structures The last two decades have seen important progress in the development of methods for the analysis of microwave and millimeter-wave passive structures, which contributed greatly to microwave integrated circuit design while also stimulating the development of new planar transmission lines.
A timely and authoritative guide to the state of the art of wave scattering Scattering of Electromagnetic Waves offers in three volumes a complete and up-to-date treatment of wave scattering by random discrete scatterers and rough surfaces.
Balanced coverage of the methodology and theory of numerical methods in finance Numerical Methods in Finance bridges the gap between financial theory and computational practice while helping students and practitioners exploit MATLAB for financial applications.
A thorough review of the most current regression methods in time series analysis Regression methods have been an integral part of time series analysis for over a century.
A significantly revised and improved introduction to a critical aspect of scientific computation Matrix computations lie at the heart of most scientific computational tasks.
A comprehensive introduction to convexity and optimization inRn This book presents the mathematics of finite dimensionalconstrained optimization problems.
Elements of Financial Time Series fills a gap in the market in the area of financial time series analysis by giving both conceptual and practical illustrations.
Designed to help motivate the learning of advanced calculus by demonstrating its relevance in the field of statistics, this successful text features detailed coverage of optimization techniques and their applications in statistics while introducing the reader to approximation theory.
An introduction to classical biostatistical methods in epidemiology Biostatistical Methods in Epidemiology provides an introduction to a wide range of methods used to analyze epidemiologic data, with a focus on nonregression techniques.
An accessible introduction to probability, stochastic processes, and statistics for computer science and engineering applicationsSecond edition now also available in Paperback.
Introducing a groundbreaking companion book to a bestselling reliability text Reliability is one of the most important characteristics defining the quality of a product or system, both for the manufacturer and the purchaser.
A comprehensive account of economic size distributions around the world and throughout the years In the course of the past 100 years, economists and applied statisticians have developed a remarkably diverse variety of income distribution models, yet no single resource convincingly accounts for all of these models, analyzing their strengths and weaknesses, similarities and differences.
Wavelet Transformations and Their Applications in Chemistry pioneers a new approach to classifying existing chemometric techniques for data analysis in one and two dimensions, using a practical applications approach to illustrating chemical examples and problems.
State-of-the-art coverage of modern computational methods for the analysis and design of beams Analysis and Design of Elastic Beams presents computer models and applications related to thin-walled beams such as those used in mechanical and aerospace designs, where thin, lightweight structures with high strength are needed.
PRAISE FOR LIGHT YEARS AND TIME TRAVEL "e;This immensely likeable work of pop science traces 'man's enduring fascination with light,' from Aristotle's plans for a death ray (burning enemy ships with a giant array of mirrors) to a recent experiment that seems to have sent Mozart's 40th Symphony faster than light, and thus back through time.
The only guide to managing and integrating the open source model With the phenomenal success of Linux, companies are taking open source business solutions much more seriously than ever before.
An introductory guide to smoothing techniques, semiparametric estimators, and their related methods, this book describes the methodology via a selection of carefully explained examples and data sets.
This book covers all the latest advances, as well as more established methods, in the application of statistical and optimisation methods within modern industry.
Interest in algorithmic trading is growing massively it s cheaper, faster and better to control than standard trading, it enables you to pre-think the market, executing complex math in real time and take the required decisions based on the strategy defined.
Meta Analysis: A Guide to Calibrating and Combining Statistical Evidence acts as a source of basic methods for scientists wanting to combine evidence from different experiments.
Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge.
Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge.
In 1989 the first edition of this book set out Gittins' pioneering index solution to the multi-armed bandit problem and his subsequent investigation of a wide of sequential resource allocation and stochastic scheduling problems.
A thorough introduction to the fundamentals of probability theory This book offers a detailed explanation of the basic models and mathematical principles used in applying probability theory to practical problems.
A thorough introduction to the fundamentals of probability theory This book offers a detailed explanation of the basic models and mathematical principles used in applying probability theory to practical problems.
In the spatial or spatio-temporal context, specifying the correct covariance function is fundamental to obtain efficient predictions, and to understand the underlying physical process of interest.
This book provides a comprehensive introduction to actuarial mathematics, covering both deterministic and stochastic models of life contingencies, as well as more advanced topics such as risk theory, credibility theory and multi-state models.
