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The Resource Advances in Latent Variables : Methods, Models and Applications

Advances in Latent Variables : Methods, Models and Applications

Label
Advances in Latent Variables : Methods, Models and Applications
Title
Advances in Latent Variables
Title remainder
Methods, Models and Applications
Creator
Contributor
Subject
Language
eng
Summary
The book, belonging to the series "Studies in Theoretical and Applied Statistics- Selected Papers from the Statistical Societies", presents a peer-reviewed selection of contributions on relevant topics organized by the editors on the occasion of the SIS 2013 Statistical Conference "Advances in Latent Variables. Methods, Models and Applications", held at the Department of Economics and Management of the University of Brescia from June 19 to 21, 2013. The focus of the book is on advances in statistical methods for analyses with latent variables. In fact, in recent years, there has been increasing interest in this broad research area from both a theoretical and an applied point of view, as the statistical latent variable approach allows the effective modeling of complex real-life phenomena in a wide range of research fields. A major goal of the volume is to bring together articles written by statisticians from different research fields, which present different approaches and experiences related to the analysis of unobservable variables and the study of the relationships between them
Member of
Cataloging source
MiAaPQ
Literary form
non fiction
Nature of contents
dictionaries
Series statement
Selected Papers of the Statistical Societies
Advances in Latent Variables : Methods, Models and Applications
Label
Advances in Latent Variables : Methods, Models and Applications
Link
http://libproxy.rpi.edu/login?url=https://ebookcentral.proquest.com/lib/rpi/detail.action?docID=2095484
Publication
Copyright
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Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Preface -- Contents -- Identification of Clusters of Variables and Underlying Latent Components in Sensory Analysis -- 1 Introduction -- 2 Methodology -- 2.1 Data Structure and Notation -- 2.2 CLV for the Clustering of the X-Variables -- 2.3 CLV with External Information on the Observations -- 2.4 CLV with External Information on the Variables -- 2.5 CLV with External Information on Both the Observations and the Variables -- 2.6 Algorithmic Point of View -- 3 Illustrative Examples -- 3.1 Clustering of Sensory Attributes in Sensory Profiling -- 3.2 L-CLV for the Segmentation of Consumers -- Conclusion -- References -- Clustering the Corpus of Seneca: A Lexical-Based Approach -- 1 Introduction -- 2 Data -- 3 Method -- 3.1 Clustering -- 3.2 Principal Component Analysis -- 4 Results and Evaluation -- 4.1 Dialogues -- 4.2 Tragedies -- 4.3 Opera Omnia -- 5 Discussion and Future Work -- References -- Modelling Correlated Consumer Preferences -- 1 Introduction -- 2 The Plackett Distribution with CUB Margins -- 2.1 The Marginal Distributions -- 2.2 The Estimation -- 3 An Empirical Application -- Concluding Remarks -- References -- Modelling Job Satisfaction of Italian Graduates -- 1 Introduction -- 2 CUB Models -- 3 Global Satisfaction and Its Components -- 4 Covariates Effects on Job Satisfaction -- Concluding Remarks -- References -- Identification of Principal Causal Effects Using Secondary Outcomes -- 1 Introduction -- 2 Framework and Notation -- 3 Some Identification Results -- 4 Identification of the Levels of the Latent Variable -- 5 An Illustrative Empirical Example -- Concluding Remarks -- References -- Dynamic Segmentation of Financial Markets: A Mixture Latent Class Markov Approach -- 1 Introduction -- 1.1 The LC Markov Model -- 2 The Data -- 3 Results -- Concluding Remarks -- References
  • Latent Class Markov Models for Measuring Longitudinal Fuzzy Poverty -- Abbreviations -- 1 Introduction -- 2 Latent Class Markov Models -- 3 Fuzzy Measures of Monetary and Non-Monetary Deprivation -- 4 Empirical Analysis -- Concluding Remarks and Further Research -- Bibliography -- A Latent Class Approach for Allocation of Employees to Local Units -- 1 Introduction -- 2 Statistical and Administrative Sources -- 3 Methodology -- 3.1 The Latent Class Model -- 3.2 The Allocation Process -- 4 Discussion and Future Works -- References -- Finding Scientific Topics Revisited -- 1 Introduction -- 2 Retrieving and Preprocessing the Corpus -- 3 Model Fitting -- 3.1 Model Selection -- 3.2 Scientific Topics and Classes -- 3.3 Hot and Cold Topics -- 3.4 Tagging Abstracts -- Conclusions -- Computational Details -- References -- A Dirichlet Mixture Model for Compositions Allowing for Dependence on the Size -- 1 Introduction -- 2 The Flexible Dirichlet Distribution -- 3 An Extension of the Flexible Dirichlet -- 3.1 The Basis -- 3.2 The Size and the Composition -- 4 Dependence Between Composition and Size -- 5 Discussion -- References -- A Latent Variable Approach to Modelling Multivariate Geostatistical Skew-Normal Data -- 1 Introduction -- 2 A Multivariate Closed Skew-Normal Geostatistical Model -- 3 Variograms and Cross-Variograms -- 4 Estimation and Prediction -- Conclusion -- Appendix -- References -- Modelling the Length of Stay of Geriatric Patients in Emilia Romagna Hospitals Using Coxian Phase-Type Distributions with Covariates -- 1 Introduction -- 2 The Coxian Phase-Type Distribution -- 3 The Data -- 4 The Results -- 4.1 The Coxian Phase-Type Distribution for the Distribution of the Length of Stay of Emilia-Romagna's Geriatric Patients -- 4.2 The Gardiner Approach: Adding the Covariates -- Conclusion -- References
  • Pathway Composite Variables: A Useful Tool for the Interpretation of Biological Pathways in the Analysis of Gene Expression Data -- 1 Introduction -- 2 Methods -- 2.1 Differential Analysis -- 2.2 Generation of Pathway Models by PCVs -- 2.3 SEM Analysis -- 2.4 Microarray Data -- 3 Results -- 4 Discussion -- References -- A Latent Growth Curve Analysis in Banking Customer Satisfaction -- 1 Introduction -- 2 Latent Growth Curve Model -- 3 Results -- Conclusions -- References -- Non-Metric PLS Path Modeling: Integration into the Labour Market of Sapienza Graduates -- 1 Introduction -- 2 PLS-PM -- 2.1 NM-PLSPM -- 2.2 Assessment of the Model -- 3 Dataset and Model -- 4 Discussion of the Results -- Conclusions -- References -- Single-Indicator SEM with Measurement Error: Case of Klein I Model -- 1 Introduction -- 2 Latent Variables in Economic Models -- 3 Single-Indicator Latent Variables with Measurement Error -- 4 Klein I Model with Latent Variables -- 5 Klein I Model Estimation with Observed Variables -- 6 Simulation of Measurement Errors for Single Indicators of Klein I Model -- 7 Application of Latent Variables in Klein I Model -- Concluding Remarks -- References -- Investigating Stock Market Behavior Using a Multivariate Markov-Switching Approach -- 1 Introduction -- 2 A Two-Step Procedure for Investigating Stock Market Behavior -- 2.1 Definition of the Groups -- 2.2 Analysis of the Dynamic Behavior -- 3 Empirical Analysis -- 3.1 Definition of the Groups -- 3.2 Analysis of the Dynamic Behavior -- Conclusions and Future Developments -- References -- A Multivariate Stochastic Volatility Model for Portfolio RiskEstimation -- 1 Introduction -- 2 Model Summary -- 3 Computational Details -- 4 Data and Results -- Conclusions -- References -- A Thick Modeling Approach to Multivariate Volatility Prediction -- 1 Introduction
  • 2 Reference Model and Combination Functions -- 2.1 The Data Generating Process -- 2.2 The Linear Combination Function -- 2.3 The Square-Root Combination Function -- 3 Estimation of the Combination Parameters -- 4 Empirical Results -- References -- Exploring Compositional Data with the Robust Compositional Biplot -- 1 Compositional Data and Their Geometry -- 2 Principal Component Analysis and the Compositional Biplot -- 3 Example -- Conclusions -- References -- Sparse Orthogonal Factor Analysis -- 1 Introduction -- 2 Sparse Factor Problem -- 3 Algorithm -- 4 Sparseness Selection -- 5 Simulation Study -- 6 Examples -- 7 Discussions -- Appendix 1: Update of n-1X [F,U] -- Appendix 2: Multiple Runs Procedure -- Appendix 3: Box Problem Data -- Bibliography -- Adjustment to the Aggregate Association Index to Minimise the Impact of Large Samples -- 1 Introduction -- 2 The Aggregate Association Index -- 2.1 Notation -- 2.2 The Index -- 3 Adjusted Aggregate Association Index -- 4 Empirical Study -- 5 Discussion -- Bibliography -- Graphical Latent Structure Testing -- 1 Introduction -- 2 Directed Acyclic Graphs with Latent Variables -- 2.1 Introducing Latent Vertices -- 2.2 Nested Constraints -- 2.3 Separation Criterion for Inequalities -- 2.4 Other Inequalities -- 3 Phylogenetic Trees -- 3.1 Phylogenetic Inequalities -- 4 Other Models -- 5 Discussion -- References -- Understanding Equity in Work Through Job Quality: A Comparative Analysis Between Disabled and Non-Disabled Graduates Using a New Composite Indicator -- Abbreviations -- 1 Job Quality and Equity in Work -- 2 Data -- 3 The Job Quality Indicator -- 4 Job Quality of Disabled and Non-Disabled Graduates -- Conclusions -- Bibliography -- Business Failure Prediction in Manufacturing: A Robust Bayesian Approach to Discriminant Scoring -- 1 Introduction -- 2 Data Description
  • 3 The Logistic Regression Model DA -- 4 Robust Bayesian Approach, RBA -- Conclusive Remarks -- References
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http://library.link/vocab/discovery_link
{'f': 'http://opac.lib.rpi.edu/record=b4383184'}
Extent
1 online resource (284 pages)
Form of item
online
Isbn
9783319029672
Media category
computer
Media MARC source
rdamedia
Media type code
c
Sound
unknown sound
Specific material designation
remote

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