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Innovations in Multivariate Statistical Modeling: Navigating Theoretical and Multidisciplinary Domains (en Inglés)
Andriëtte Bekker
(Ilustrado por)
·
Johannes T. Ferreira
(Ilustrado por)
·
Mohammad Arashi
(Ilustrado por)
·
Springer
· Tapa Dura
Innovations in Multivariate Statistical Modeling: Navigating Theoretical and Multidisciplinary Domains (en Inglés) - Bekker, Andriëtte ; Ferreira, Johannes T. ; Arashi, Mohammad
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Reseña del libro "Innovations in Multivariate Statistical Modeling: Navigating Theoretical and Multidisciplinary Domains (en Inglés)"
Preface.- PART 1: Trends in Multi- and Matrix-Variate Analysis.- Q. Guo, X. Deng and N. Ravishanker: Association-based Optimal Subpopulation Selection of Multivariate Data.- T. B. Mattos, L. A. Matos, V. H Lachos Aldo: Likelihood-Based Inference For Linear Mixed-Effects Models With Censored Response Using Skew-Normal Distribution.- Y. Melnykov, M. Perry, V. Melnykov: Robust Estimation of Multiple Change Points in Multivariate Processes.- T. Botha, J. T Ferreira and A. Bekker: Some Computational Aspects Of A Noncentral Dirichlet Family.- Y. Murat Bulut and Olcay Arslan: Modeling Handwritten Digits Dataset Using The Matrix Variate T Distribution.- B. Byukusenge, D. von Rosen and M. Singull: On The Identification Of Extreme Elements In A Residual For The Gmanova-Manova Model.- M. Billio, R. Casarin, M. Costola and M. Iacopini: Matrix-variate Smooth Transition Models for Temporal Networks.- H. Baghishani and J. Ownuk: A Flexible Matrix-Valued Response Regression For Skewed Data.- J. Trink, H. Haghbin and M. Maadooliat: Multivariate Functional Singular Spectrum Analysis: A Nonparametric Approach for Analyzing Functional Time Series.- M. Greenacre: Compositional Data Analysis - Linear Algebra, Visualization And Interpretation.- A. Alzaatreh, F. Famoye and C. Lee: Multivariate Count Data Regression Models And Their Applications.- A. Iranmanesh, M. Rafiei and D. Nagar: A Generalized Multivariate Gamma Distribution.- PART 2: Aspects of High Dimensional Methodology and Bayesian Learning .- G. D' Angella and C. Hennig: A Comparison Of Different Clustering Approaches For High-Dimensional Presence-Absence Data.- S. Millard, M. Arashi and G. Maribe: High-Dimensional Feature Selection For Logistic Regression Using Blended Penalty Functions.- I. Munaweera, S. Muthukumarana and M. Jafari Jozani: A Generalized Quadratic Garrote Approach Towards Ridge Regression Analysis.- M. Roozbeh: High Dimensional Nonlinear Optimization Problem In Semiparametric Regression Model.- PART 3: Frontiers in Robust Analysis and Mixture Modelling.- A. Punzo and S. D. Tomarchia: Parsimonious Finite Mixtures Of Matrix-Variate Regressions.- F. Zehra Doğru and Olcay Arslan: Robust Multivariate Modelling for Heterogeneous Data Sets With Mixtures of Multivariate Skew Laplace Normal Distributions.- M. Norouzirad, M. Arashi, F. J Marques and F. Esmaeili: Robust Estimation Through Preliminary Testing Based On The Lad-Lasso
