Recent Developments in Multivariate and Random Matrix Analysis: Festschrift in Honour of Dietrich Von Rosen, Holgersson Thomas, Singull Martin
Автор: Gregory R. Hancock, Jeffrey R. Harring, George B. Macready Название: Advances in Latent Class Analysis: A Festschrift in Honor of C. Mitchell Dayton ISBN: 1641135611 ISBN-13(EAN): 9781641135610 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 7623.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: What is latent class analysis? If you asked that question thirty or forty years ago you would have gotten a different answer than you would today. Closer to its time of inception, latent class analysis was viewed primarily as a categorical data analysis technique, often framed as a factor analysis model where both the measured variable indicators and underlying latent variables are categorical. Today, however, it rests within much broader mixture and diagnostic modeling framework, integrating measured and latent variables that may be categorical and/or continuous, and where latent classes serve to define the subpopulations for whom many aspects of the focal measured and latent variable model may differ. For latent class analysis to take these developmental leaps required contributions that were methodological, certainly, as well as didactic. Among the leaders on both fronts was C. Mitchell “Chan” Dayton, at the University of Maryland, whose work in latent class analysis spanning several decades helped the method to expand and reach its current potential. The current volume in the Center for Integrated Latent Variable Research (CILVR) series reflects the diversity that is latent class analysis today, celebrating work related to, made possible by, and inspired by Chan’s noted contributions, and signaling the even more exciting future yet to come.
Автор: Gregory R. Hancock, Jeffrey R. Harring, George B. Macready Название: Advances in Latent Class Analysis: A Festschrift in Honor of C. Mitchell Dayton ISBN: 164113562X ISBN-13(EAN): 9781641135627 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 14276.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: What is latent class analysis? If you asked that question thirty or forty years ago you would have gotten a different answer than you would today. Closer to its time of inception, latent class analysis was viewed primarily as a categorical data analysis technique, often framed as a factor analysis model where both the measured variable indicators and underlying latent variables are categorical. Today, however, it rests within much broader mixture and diagnostic modeling framework, integrating measured and latent variables that may be categorical and/or continuous, and where latent classes serve to define the subpopulations for whom many aspects of the focal measured and latent variable model may differ. For latent class analysis to take these developmental leaps required contributions that were methodological, certainly, as well as didactic. Among the leaders on both fronts was C. Mitchell “Chan” Dayton, at the University of Maryland, whose work in latent class analysis spanning several decades helped the method to expand and reach its current potential. The current volume in the Center for Integrated Latent Variable Research (CILVR) series reflects the diversity that is latent class analysis today, celebrating work related to, made possible by, and inspired by Chan’s noted contributions, and signaling the even more exciting future yet to come.
Описание: The collection and analysis of data play an important role in many fields of science and technology, such as computational biology, quantitative finance, information engineering, machine learning, neuroscience, medicine, and the social sciences.
Описание: The articles in this collection are a sampling of some of the research presented during the conference "Stochastic Analysis and Related Topics", held in May of 2015 at Purdue University in honor of the 60th birthday of Rodrigo Banuelos.
Автор: Adachi Kohei Название: Matrix-Based Introduction to Multivariate Data Analysis ISBN: 9811541027 ISBN-13(EAN): 9789811541025 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Elementary matrix operations.- Intravariable statistics.- Inter-variable statistics.- Regression analysis.- Principal component analysis.- Principal component.
Описание: Contains articles which provides an account of developments in contemporary white noise analysis and some of its applications. This book emphasises the connections of white noise analysis with branches of contemporary probability, including stochastic geometry, the structure theory of stationary Gaussian processes, and large deviations.
Автор: Adachi Kohei Название: Matrix-Based Introduction to Multivariate Data Analysis ISBN: 9811095957 ISBN-13(EAN): 9789811095955 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Part 1. Elementary Statistics with Matrices.- 1 Introduction to Matrix Operations.- 2 Intra-variable Statistics.- 3 Inter-variable Statistics.- Part 2. Least Squares Procedures.- 4 Regression Analysis.- 5 Principal Component Analysis (Part 1).- 6 Principal Component Analysis 2 (Part 2).- 7 Cluster Analysis.- Part 3. Maximum Likelihood Procedures.- 8 Maximum Likelihood and Normal Distributions.- 9 Path Analysis.- 10 Confirmatory Factor Analysis.- 11 Structural Equation Modeling.- 12 Exploratory Factor Analysis.- Part 4. Miscellaneous Procedures.- 13 Rotation Techniques.- 14 Canonical Correlation and Multiple Correspondence Analyses.- 15 Discriminant Analysis.- 16 Multidimensional Scaling.- Appendices.- A1 Geometric Understanding of Matrices and Vectors.- A2 Decomposition of Sums of Squares.- A3 Singular Value Decomposition (SVD).- A4 Matrix Computation Using SVD.- A5 Supplements for Probability Densities and Likelihoods.- A6 Iterative Algorithms.- References.- Index.
Описание: Preface.- Contents.- List of Contributors.- On Nearly Linear Recurrence Sequences, Shigeki Akiyama, Jan-Hendrik Evertse and Attila Pethц.- Risk Theory with Affine Dividend Payment Strategies, Hansjцrg Albrecher and Arian Cani.- A Discrepancy Problem: Balancing Infinite Dimensional Vectors, Jуzsef Beck.- Squares with Three Nonzero Digits, Michael A. Bennett and Adrian-Maria Scheerer.- On the density of coprime tuples of the form (n; bf1(n)c; : bfk(n)c), where f1; : fk are functions from a Hardy field, Vitaly Bergelson and Florian Karl Richter.- On the uniform theory of lacunary series, Istvбn Berkes.- Diversity in Parametric Families of Number Fields, Yuri Bilu and Florian Luca.- Local Oscillations in Moderately Dense Sequences of Primes, Jцrg Brьdern and Christian Elsholtz.- Sums of the digits in bases 2 and 3, Jean-Marc Deshouillers, Laurent Habsieger, Shanta Laishram and Bernard Landreau.- On the Discrepancy of Halton-Kronecker Sequences, Michael Drmota, Roswitha Hofer and Gerhard Larcher.- More on Diophantine Sextuples, Andrej Dujella and Matija Kazalicki.- Effective Results for Discrimant Equations Over Finitely Generated Integral Domains, Jan-Hendrik Evertse and Kбlmбn Gyцry.- Quasi-equivalence of Heights and Runge's Theorem, Philipp Habegger.- On the Monoid Generated by a Lucas Sequence, Clemens Heuberger and Stephan Wagner.- Measures of pseudorandomness: Arithmetic Autocorrelation and correlation Measure, Richard Hofer, Lбszlу Mйrai and Arne Winterhof.- On Multiplicative Independent Bases for Canonical Number Systems in Cyclotomic Number Fields, Manfred G. Madritsch, Paul Surer and Volker Ziegler.- Refined Estimates for Exponential Sums and a Problem Concerning the Product of Three L-Series, Werner Georg Nowak.- Orbits of Algebraic Dynamical Systems in Subgroups and Subfields, Alina Ostafe and Igor E. Shparlinski.- Patterns of Primes in Arithmetic Progressions, Jбnos Pintz.- On Simple Linear Recurrences, Andrzej Schinzel.- Equivalence of the Logarithmically Averaged Chowla and Sarnak Conjectures, Terence Tao.- Discrepancy Bounds for -Adic Halton Sequences, Jцrg M. Thuswaldner.
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