This book presents a new set of embedded system design techniques called multidimensional data flow, which combine the various benefits offered by existing methodologies such as block-based system des
A summary of past work and a description of new approaches to thinking about kriging, commonly used in the prediction of a random field based on observations at some set of locations in mining, hydrol
Modelling and Forecasting Financial Data brings together a coherent and accessible set of chapters on recent research results on this topic. To make such methods readily useful in practice, the contri
This book analyzes the verification of empirical asset pricing models when returns of securities are projected onto a set of presumed (or observed) factors. Particular emphasis is placed on the verifi
This volume gathers seminal contributions that identify the boundaries of the various ethical dilemmas that have emerged in the field of big data research and proposes a set of guidelines for solving
Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, high
Regarding the set of all feature attributes in a given database as the universal set, this monograph discusses various nonadditive set functions that describe the interaction among the contributions f
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 gr
This book presents the reader with a set of diverse, carefully developed and clearly specified systems of transcription and coding, arising from contrasting theoretical perspectives, and presented as
A complete set of statistical tools for beginning financial analysts from a leading authority Written by one of the leading experts on the topic, An Introduction to Analysis of Financial Data with R e
This book illustrates a set of tools - story grammars, relational data models, and network models - that can be profitably used for the collection, organization, and analysis of narrative data in socio-historical research. A story grammar, or Subject-Action-Object and their modifiers, is the linguistic tool the author uses to structure narrative for the purpose of collecting event data. Relational database models make such complex data collection schemes practically feasible in a computer environment. Finally, network models are a statistical tool best suited to analyze this type of data. Driven by the metaphors of the journal (from … to) and the alchemy (words into numbers), the book leads the reader throughout a number of paths, from substantive to methodological issues, across time and disciplines: sociology, linguistics, literary criticism, history, statistics, computer science, philosophy, cognitive psychology, political science.
Risk has always been central to finance, and managing risk depends critically on information. As evidenced by recent events, the need has never been greater for skills, systems and methodologies to manage risk information in financial markets. Authored by leading figures in risk management and analysis, this handbook serves as a unique and comprehensive reference for the technical, operational, regulatory and political issues in collecting, measuring and managing financial data. It will appeal to a wide range of audiences, from financial industry practitioners and regulators responsible for implementing risk management systems, to system integrators and software firms helping to improve such systems. Volume I examines the business and regulatory context that makes risk information so important. A vast set of techniques and processes have grown up over time, and without an understanding of the broader forces at work, it is all too easy to get lost in the details.
This book illustrates a set of tools - story grammars, relational data models, and network models - that can be profitably used for the collection, organization, and analysis of narrative data in socio-historical research. A story grammar, or Subject-Action-Object and their modifiers, is the linguistic tool the author uses to structure narrative for the purpose of collecting event data. Relational database models make such complex data collection schemes practically feasible in a computer environment. Finally, network models are a statistical tool best suited to analyze this type of data. Driven by the metaphors of the journal (from … to) and the alchemy (words into numbers), the book leads the reader throughout a number of paths, from substantive to methodological issues, across time and disciplines: sociology, linguistics, literary criticism, history, statistics, computer science, philosophy, cognitive psychology, political science.
Provides information on storing and retrieving application data, covering such topics as creating a data model, working with data objects, refining the results set, versioning and migrating data, and
Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.
Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.
The future of the health care industry rests on advanced analyticsHealth Data's Destiny provides a visionary overview of how advanced analytics is set to transform the health care industry. B
This fourth volume marks the definitive publication of the most important fossil finds in palaeoanthropology: Olduvai hominids 7. 13, 16 and 24 (popularly known to workers in the field as Jonny's Child, Cindy, George and Twiggy). Found from 1960 in Olduvai Gorge and dating from 1.9 to 1.6 million years ago, they were identified in 1964 by Louis Leakey and the author amidst great controversy as a hitherto unrecognised species of the genus Homo, named by then Homo habilis on account of its apparent tool-making abilities. Professor Tobias develops this conclusion through extensive analysis of the cranial and endocranial material and teeth and comparison with a treasury of data, much of its original, on early hominds from South and East Africa, Asia and Europe, as well as modern human and anthropoid ape specimens. He offers a substantial exploration of the place of Homo habilis in human evolution, its status in relation to the australopithecines and Homo erectus and its apparent capacity f
An up-to-date, detailed set of notes covering all aspects of NOAA AVHRR data collection, pre-processing, analysis and application. Includes many FTP sites, e-mail addresses and URL locations. Some cha
