Multidimensional Analysis
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Author | : George W. Hart |
Publisher | : Springer Science & Business Media |
Total Pages | : 242 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 1461242088 |
This book deals with the mathematical properties of dimensioned quantities, such as length, mass, voltage, and viscosity. Beginning with a careful examination of how one expresses the numerical results of a measurement and uses these results in subsequent manipulations, the author rigorously constructs the notion of dimensioned numbers and discusses their algebraic structure. The result is a unification of linear algebra and traditional dimensional analysis that can be extended from the scalars to which the traditional analysis is perforce restricted to multidimensional vectors of the sort frequently encountered in engineering, systems theory, economics, and other applications.
Author | : Louis-Marie Asselin |
Publisher | : Springer Science & Business Media |
Total Pages | : 215 |
Release | : 2009-08-29 |
Genre | : Business & Economics |
ISBN | : 1441908439 |
Poverty is a paradoxical state. Recognizable in the eld for any sensitive observer who travels in remote rural areas and urban slums and meets marginalized people in a given society, poverty still remains a challenge to conceptual formalization and to measurement that is consistent with such formalization. The analysis of poverty is multidisciplinary. It goes from ethics to economics, from political science to human biology, and any type of measurement rests on mathematics. Moreover, poverty is multifaceted according to the types of deprivation, and it is also gender and age speci c. A vector of variables is required, which raises a substantial problem for individual and group comparisons necessary to equity analysis. Multidimension- ity also complicates the aggregation necessary to perform the ef ciency analysis of policies. In the case of income poverty, these two problems, equity and ef ciency, have bene ted from very signi cant progress in the eld of economics. Similar achievements are still to come in the area of multidimensional poverty. Within this general background, this book has a very modest and narrow-scoped objective. It proposes an operational methodology for measuring multidimensional poverty, independent from the conceptual origin, the size and the qualitative as well as the quantitative nature of the primary indicators used to describe the poverty of an individual, a household or a sociodemographic entity.
Author | : Joseph B. Kruskal |
Publisher | : SAGE Publications |
Total Pages | : 100 |
Release | : 1978-01-01 |
Genre | : Social Science |
ISBN | : 1506320880 |
Outlines a set of techniques that enables a researcher to explore the hidden structure of large databases. These techniques use proximities to find a configuration of points that reflect the structure in the data.
Author | : J. J. Duistermaat |
Publisher | : Cambridge University Press |
Total Pages | : 444 |
Release | : 2004-05-06 |
Genre | : Mathematics |
ISBN | : 1139451197 |
Part one of the authors' comprehensive and innovative work on multidimensional real analysis. This book is based on extensive teaching experience at Utrecht University and gives a thorough account of differential analysis in multidimensional Euclidean space. It is an ideal preparation for students who wish to go on to more advanced study. The notation is carefully organized and all proofs are clean, complete and rigorous. The authors have taken care to pay proper attention to all aspects of the theory. In many respects this book presents an original treatment of the subject and it contains many results and exercises that cannot be found elsewhere. The numerous exercises illustrate a variety of applications in mathematics and physics. This combined with the exhaustive and transparent treatment of subject matter make the book ideal as either the text for a course, a source of problems for a seminar or for self study.
Author | : Sabina Alkire |
Publisher | : OUP Oxford |
Total Pages | : 369 |
Release | : 2015-06-04 |
Genre | : Business & Economics |
ISBN | : 0191003638 |
Multidimensional poverty measurement and analysis is evolving rapidly. Notably, it has informed the publication of the Multidimensional Poverty Index (MPI) estimates in the Human Development Reports of the United Nations Development Programme since 2010, and the release of national poverty measures in Mexico, Colombia, Bhutan, the Philippines and Chile. The academic response has been similarly swift, with related articles published in both theoretical and applied journals. The high and insistent demand for in-depth and precise accounts of multidimensional poverty measurement motivates this book, which is aimed at graduate students in quantitative social sciences, researchers of poverty measurement, and technical staff in governments and international agencies who create multidimensional poverty measures. The book is organized into four elements. The first introduces the framework for multidimensional measurement and provides a lucid overview of a range of multidimensional techniques and the problems each can address. The second part gives a synthetic introduction of 'counting' approaches to multidimensional poverty measurement and provides an in-depth account of the counting multidimensional poverty measurement methodology developed by Alkire and Foster, which is a straightforward extension of the well-known Foster-Greer-Thorbecke poverty measures that had a significant and lasting impact on income poverty measurement. The final two parts deal with the pre-estimation issues such as normative choices and distinctive empirical techniques used in measure design, and the post-estimation issues such as robustness tests, statistical inferences, comparisons over time, and assessments of inequality among the poor.
Author | : I. Borg |
Publisher | : Springer Science & Business Media |
Total Pages | : 402 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 1461247683 |
Multidimensional Similarity Structure Analysis comprises a class of models that represent similarity among entities (for example, variables, items, objects, persons, etc.) in multidimensional space to permit one to grasp more easily the interrelations and patterns present in the data. The book is oriented to both researchers who have little or no previous exposure to data scaling and have no more than a high school background in mathematics and to investigators who would like to extend their analyses in the direction of hypothesis and theory testing or to more intimately understand these analytic procedures. The book is repleted with examples and illustrations of the various techniques drawn largely, but not restrictively, from the social sciences, with a heavy emphasis on the concrete, geometric or spatial aspect of the data representations.
Author | : Aleksei A. Dezin |
Publisher | : CRC Press |
Total Pages | : 188 |
Release | : 2018-01-18 |
Genre | : Mathematics |
ISBN | : 135109176X |
Multidimensional Analysis and Discrete Models, a thorough and detailed reference, covers the main structures of multidimensional analysis and the intrinsically defined discrete models in applied mathematics, mathematical physics, and related fields. The material is presented in a clear and straightforward manner, with background information provided to define finite models and to clarify the concepts of multidimensional analysis. The book covers special difference models of the mathematical physics equations, models of boundary value problems, and objects of quantum mechanics. Considerable attention is also given to differential operators on Riemannian manifolds and the interpretation of classical vector analysis. The primary focus of Multidimensional Analysis and Discrete Models is on the description of regular methods of constructing intrinsically defined discrete models for special classes of continual objects, but emphasis is also given to the interaction of ideas and methods that exist throughout the field of mathematics. For example, the connections between theories derived from classical and functional analysis, Riemannian geometry, and algebraic topology are illustrated, and are discussed in terms of their relevance to computing solutions.
Author | : Tony Berber Sardinha |
Publisher | : Bloomsbury Publishing |
Total Pages | : 304 |
Release | : 2019-03-21 |
Genre | : Language Arts & Disciplines |
ISBN | : 1350023833 |
Multi-Dimensional Analysis: Research Methods and Current Issues provides a comprehensive guide both to the statistical methods in Multi-Dimensional Analysis (MDA) and its key elements, such as corpus building, tagging, and tools. The major goal is to explain the steps involved in the method so that readers may better understand this complex research framework and conduct MD research on their own. Multi-Dimensional Analysis is a method that allows the researcher to describe different registers (textual varieties defined by their social use) such as academic settings, regional discourse, social media, movies, and pop songs. Through multivariate statistical techniques, MDA identifies complementary correlation groupings of dozens of variables, including variables which belong both to the grammatical and semantic domains. Such groupings are then associated with situational variables of texts like information density, orality, and narrativity to determine linguistic constructs known as dimensions of variation, which provide a scale for the comparison of a large number of texts and registers. This book is a comprehensive research guide to MDA.
Author | : Ingwer Borg |
Publisher | : Springer Science & Business Media |
Total Pages | : 469 |
Release | : 2013-04-18 |
Genre | : Mathematics |
ISBN | : 1475727119 |
Multidimensional scaling (MDS) is a technique for the analysis of similarity or dissimilarity data on a set of objects. Such data may be intercorrelations of test items, ratings of similarity on political candidates, or trade indices for a set of countries. MDS attempts to model such data as distances among points in a geometric space. The main reason for doing this is that one wants a graphical display of the structure of the data, one that is much easier to understand than an array of numbers and, moreover, one that displays the essential information in the data, smoothing out noise. There are numerous varieties of MDS. Some facets for distinguishing among them are the particular type of geometry into which one wants to map the data, the mapping function, the algorithms used to find an optimal data representation, the treatment of statistical error in the models, or the possibility to represent not just one but several similarity matrices at the same time. Other facets relate to the different purposes for which MDS has been used, to various ways of looking at or "interpreting" an MDS representation, or to differences in the data required for the particular models. In this book, we give a fairly comprehensive presentation of MDS. For the reader with applied interests only, the first six chapters of Part I should be sufficient. They explain the basic notions of ordinary MDS, with an emphasis on how MDS can be helpful in answering substantive questions.
Author | : William G. Jacoby |
Publisher | : SAGE |
Total Pages | : 100 |
Release | : 1991 |
Genre | : Mathematics |
ISBN | : 9780803941786 |
For many readers, data theory is probably unfamiliar. Data isn't usually the subject matter of theory in and of itself. However, in this volume, William Jacoby introduces a theory of data idea. It examines how real world observations are transformed into something to be analyzed that is, data. Jacoby explores some of the basic ideas of data theory, and considers their implications for research strategies in the social sciences. "Like others in the series, it is reassuringly slim. It is intended for a general social science readership and is a worthwhile read even for experienced data analysts. since it draws attention not only to often overlooked assumptions, but also to often ignored analysis possibilities." --Telephone Surveys "On the whole, this book contains a lot of useful information." --Journal of Classification