Books in Statistics and probability

Contributions to Survey Sampling and Applied Statistics

1st Edition
May 10, 2014
H. O. Hartley
H. A. David
English
eBook
9 7 8 1 4 8 3 2 6 0 8 8 4

Contributions to Survey Sampling and Applied Statistics: Papers in Honor of H. O. Hartley covers the significant advances in survey sampling, modeling, and applied statistics. This book is organized into five parts encompassing 20 chapters. The opening part looks into some aspects of statistics, sampling, randomization, predictive estimation, and internal congruency. This part also considers the properties of variance estimation for a specified multiple frame survey design and some sampling designs involving unequal probabilities of selection and robust estimation of a finite population total. The next parts present the analysis and the theoretical and practical aspects of linear models, as well as the applications of time series analysis. These topics are followed by discussions of the testing for outliers in linear regression; the robustness of location estimators; and completeness comparisons among sample sequences. The closing part deals with the properties of norm estimators in regression and geometric programming. This part also provides tables of the normal conditioned on t-distribution. This book will prove useful to mathematicians and statisticians.

Stochastic Modelling of Social Processes

1st Edition
May 10, 2014
Andreas Diekmann + 1 more
English
eBook
9 7 8 1 4 8 3 2 6 6 5 6 5

Stochastic Modelling of Social Processes provides information pertinent to the development in the field of stochastic modeling and its applications in the social sciences. This book demonstrates that stochastic models can fulfill the goals of explanation and prediction. Organized into nine chapters, this book begins with an overview of stochastic models that fulfill normative, predictive, and structural–analytic roles with the aid of the theory of probability. This text then examines the study of labor market structures using analysis of job and career mobility, which is one of the approaches taken by sociologists in research on the labor market. Other chapters consider the characteristic trends and patterns from data on divorces. This book discusses as well the two approaches of stochastic modeling of social processes, namely competing risk models and semi-Markov processes. The final chapter deals with the practical application of regression models of survival data. This book is a valuable resource for social scientists and statisticians.

Stochastic Analysis

1st Edition
May 10, 2014
Eddy Mayer-Wolf + 2 more
English
eBook
9 7 8 1 4 8 3 2 1 8 7 0 0

Stochastic Analysis: Liber Amicorum for Moshe Zakai focuses on stochastic differential equations, nonlinear filtering, two-parameter martingales, Wiener space analysis, and related topics. The selection first ponders on conformally invariant and reflection positive random fields in two dimensions; real time architectures for the Zakai equation and applications; and quadratic approximation by linear systems controlled from partial observations. Discussions focus on predicted miss, review of basic sequential detection problems, multigrid algorithms for the Zakai equation, invariant test functions and regularity, and reflection positivity. The text then takes a look at a model of stochastic differential equation in Hubert spaces applicable to Navier Stokes equation in dimension 2; wavelets as attractors of random dynamical systems; and Markov properties for certain random fields. The publication examines the anatomy of a low-noise jump filter, nonlinear filtering with small observation noise, and closed form characteristic functions for certain random variables related to Brownian motion. Topics include derivation of characteristic functions for the examples, proof of the theorem, sequential quadratic variation test, asymptotic optimal filters, mean decision time, and asymptotic optimal filters. The selection is a valuable reference for researchers interested in stochastic analysis.

Classification and Clustering

1st Edition
May 10, 2014
J. Van Ryzin
English
eBook
9 7 8 1 4 8 3 2 7 6 6 1 8

Classification and Clustering documents the proceedings of the Advanced Seminar on Classification and Clustering held in Madison, Wisconsin on May 3-5, 1976. This compilation discusses the relationship between multidimensional scaling and clustering, distribution problems in clustering, and botryology of botryology. The graph theoretic techniques for cluster analysis algorithms, data dependent clustering techniques, and linguistic approach to pattern recognition are also elaborated. This text likewise covers the discriminant analysis when scale contamination is present in the initial sample and statistical basis of computerized diagnosis using the electrocardiogram. Other topics include the simple histogram method for nonparametric classification and optimal smoothing of density estimates. This book is intended for mathematicians, biological scientists, social scientists, computer scientists, statisticians, and engineers interested in classification and clustering.

Graphical Representation of Multivariate Data

1st Edition
May 10, 2014
Peter C. C. Wang
English
eBook
9 7 8 1 4 8 3 2 7 3 9 6 9

Graphical Representation of Multivariate Data is a collection of papers that explores and expands the use of graphical methods to represent multivariate data. One paper explains the application of the graphical representation of k-dimensional data technique as a statistical tool to analyze Soviet foreign policy. The technique encompasses data files, data modifications, and transformations of Soviet foreign policy in 25 countries from 1964 to 1975. The Faces methodology (a representation of multidimensional data developed by Herman Chernoff) analyzes ten sets of these data. Another paper describes the Faces techniques, Andrew's sine curves, Anderson's metroglyphs, which are then compared to Facial representations. Examples show the application of Chernoff Faces at the Los Alamos Scientific Laboratory. The paper considers the technique's main drawback—subjectivit... a positive feature that can be overcome. Another paper agrees that computer-generated faces are a good representations to induce actions on tasks based on multivariate metrical data, The paper also acknowledges that the stereotyping of faces can be useful when making a display. One paper investigates the responsiveness to facial and verbal cues using the Syracuse person perception tool as a measuring tool. The collection is suitable for investigators, professors, or students in mathematics, computer science, or engineering courses. It will also be very helpful for researchers involved in graphical display of multivariate data from a wide range of different fields such as statistics, economics, regional planning, clinical research, social/political science, psychiatric studies, international relations, international trade, and arms transfer.

Frontiers of Pattern Recognition

1st Edition
May 10, 2014
Satosi Watanabe
English
eBook
9 7 8 1 4 8 3 2 6 8 9 4 1

Frontiers of Pattern Recognition contains the proceedings of the International Conference on Frontiers of Pattern Recognition which took place on January 18-20, 1971, at the University of Hawaii, Honolulu. The compendium consists of 30 papers from authorities from eleven different countries, which describe the frontiers of pattern recognition as viewed from diverse viewpoints. Topics discussed include some techniques for recognizing structures in pictures, grammatical inference, syntactic pattern recognition and stochastic languages, and pattern cognition and the organization of information. Also covered are subjects on human face recognition, cluster analysis, and learning algorithms of pattern recognition in non-stationary conditions. Computer scientists, mathematicians, statisticians, linguists, and psychologists will find the book informative.

Introductory Statistics for the Behavioral Sciences

1st Edition
May 10, 2014
Joan Welkowitz + 2 more
English
eBook
9 7 8 1 4 8 3 2 5 8 1 5 7

Introductory Statistics for the Behavioral Sciences provides an introduction to statistical concepts and principles. This book emphasizes the robustness of parametric procedures wherein such significant tests as t and F yield accurate results even if such assumptions as equal population variances and normal population distributions are not well met. Organized into three parts encompassing 16 chapters, this book begins with an overview of the rationale upon which much of behavioral science research is based, namely, drawing inferences about a population based on data obtained from a sample. This text then examines the primary goal of descriptive statistics to bring order out of chaos. Other chapters consider the concept of variability and its applications. This book discusses as well the essential characteristics of a group of scores. The final chapter deals with the chi-square analysis. This book is a valuable resource for students of statistics as well as for undergraduates majoring in psychology, sociology, and education.

Applied Stochastic Processes

1st Edition
May 9, 2014
G. Adomian
English
eBook
9 7 8 1 4 8 3 2 5 9 0 8 6

Applied Stochastic Processes is a collection of papers dealing with stochastic processes, stochastic equations, and their applications in many fields of science. One paper discusses stochastic systems involving randomness in the system itself that can be a large dynamical multi-input, multi-output system. Examples of a large system are the national economy of a major country or when an acoustic wave is propagating as in the atmosphere, ocean, or sea. Another paper proves that only the average properties of the molecules of biology can be measured with precision in the test tube; and disputes a "simplistic" model of the cell as defined by a miniature Laplaces' universe. The paper notes that the way existing cells are constructed implies that quantum mechanical principles lead to certain questions (about simple experiments) having only statistical answers. Another paper addresses the detection of distributed, fluctuating targets in a reverberation limited, randomly time, and space varying transmission media. This approach is done by using the concepts of "random Green's functions" and the "stochastic Green's function." The collection will prove useful for cellular researchers, mathematicians, physicist, engineers, and academicians in the field of applied mathematics, statistics, and chemistry.

Statistical Analysis

1st Edition
May 9, 2014
A. A. Afifi + 1 more
English
eBook
9 7 8 1 4 8 3 2 6 0 7 1 6

Statistical Analysis: A Computer Oriented Approach discusses the probabilistic foundations of statistics, the standard statistical inference procedures, regression, and correlation analysis. The book also explains the analysis of variance and multivariate analysis, with an emphasis on the applications and interpretations of statistical tools. The text defines computer terminologies, coding sheets, format statements, and packaged statistical programs or software. Software and other related programs are tools for data analysis: the "frequency count program" analyzes discrete observations; and the "descriptive program" investigates one continuous variable. Other similar tools are the "descriptive program with strata" that evaluates more than one continuous random variable, and the "crosstabulation program" that reviews contingency tables. The book also explains the general linear model which is applied to the estimators and tests of hypotheses for simple and multiple linear regression models. The text shows how different packaged computer programs can be used to perform analyses of variance. For example, the factorial programs can analyze special designs of randomized blocks, replicated randomized blocks, and nested designs. For other special designs, including the split plot and Latin square designs, the investigator can make adaptations to the standard factorial program. The book is intended for students of statistical inference, computer programming, and readers interested in advanced mathematics.

An Introduction to Measure-Theoretic Probability

2nd Edition
March 19, 2014
George G. Roussas
English
Hardback
9 7 8 0 1 2 8 0 0 0 4 2 7
eBook
9 7 8 0 1 2 8 0 0 2 9 0 2

An Introduction to Measure-Theoretic Probability, Second Edition, employs a classical approach to teaching the basics of measure theoretic probability. This book provides in a concise, yet detailed way, the bulk of the probabilistic tools that a student working toward an advanced degree in statistics, probability and other related areas should be equipped with. This edition requires no prior knowledge of measure theory, covers all its topics in great detail, and includes one chapter on the basics of ergodic theory and one chapter on two cases of statistical estimation. Topics range from the basic properties of a measure to modes of convergence of a sequence of random variables and their relationships; the integral of a random variable and its basic properties; standard convergence theorems; standard moment and probability inequalities; the Hahn-Jordan Decomposition Theorem; the Lebesgue Decomposition T; conditional expectation and conditional probability; theory of characteristic functions; sequences of independent random variables; and ergodic theory. There is a considerable bend toward the way probability is actually used in statistical research, finance, and other academic and nonacademic applied pursuits. Extensive exercises and practical examples are included, and all proofs are presented in full detail. Complete and detailed solutions to all exercises are available to the instructors on the book companion site. This text will be a valuable resource for graduate students primarily in statistics, mathematics, electrical and computer engineering or other information sciences, as well as for those in mathematical economics/finance in the departments of economics.

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