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001451965 019__ $$a1355267858
001451965 020__ $$a9783031139710$$q(electronic bk.)
001451965 020__ $$a3031139712$$q(electronic bk.)
001451965 020__ $$z3031139704
001451965 020__ $$z9783031139703
001451965 0247_ $$a10.1007/978-3-031-13971-0$$2doi
001451965 035__ $$aSP(OCoLC)1356007783
001451965 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE$$dYDX$$dUKAHL
001451965 049__ $$aISEA
001451965 050_4 $$aQA278
001451965 08204 $$a519.5/35$$223/eng/20230106
001451965 24500 $$aInnovations in multivariate statistical modeling :$$bnavigating theoretical and multidisciplinary domains /$$cAndriëtte Bekker, Johannes T. Ferreira, Mohammad Arashi, Ding-Geng Chen, editors.
001451965 260__ $$aCham :$$bSpringer,$$c2022.
001451965 300__ $$a1 online resource (434 p.).
001451965 4901_ $$aEmerging topics in statistics and biostatistics
001451965 5050_ $$aPreface -- 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 Dogru 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.
001451965 506__ $$aAccess limited to authorized users.
001451965 520__ $$aMultivariate statistical analysis has undergone a rich and varied evolution during the latter half of the 20th century. Academics and practitioners have produced much literature with diverse interests and with varying multidisciplinary knowledge on different topics within the multivariate domain. Due to multivariate algebra being of sustained interest and being a continuously developing field, its appeal breaches laterally across multiple disciplines to act as a catalyst for contemporary advances, with its core inferential genesis remaining in that of statistics. It is exactly this varied evolution caused by an influx in data production, diffusion, and understanding in scientific fields that has blurred many lines between disciplines. The cross-pollination between statistics and biology, engineering, medical science, computer science, and even art, has accelerated the vast amount of questions that statistical methodology has to answer and report on. These questions are often multivariate in nature, hoping to elucidate uncertainty on more than one aspect at the same time, and it is here where statistical thinking merges mathematical design with real life interpretation for understanding this uncertainty. Statistical advances benefit from these algebraic inventions and expansions in the multivariate paradigm. This contributed volume aims to usher novel research emanating from a multivariate statistical foundation into the spotlight, with particular significance in multidisciplinary settings. The overarching spirit of this volume is to highlight current trends, stimulate a focus on, and connect multidisciplinary dots from and within multivariate statistical analysis. Guided by these thoughts, a collection of research at the forefront of multivariate statistical thinking is presented here which has been authored by globally recognized subject matter experts.
001451965 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed January 6, 2023).
001451965 650_0 $$aMultivariate analysis.
001451965 655_0 $$aElectronic books.
001451965 7001_ $$aBekker, Andriëtte,$$d1958-
001451965 7001_ $$aFerreira, Johannes T.
001451965 7001_ $$aArashi, M.$$q(Mohammad),$$d1981-
001451965 7001_ $$aChen, Ding-Geng.
001451965 77608 $$iPrint version:$$aBekker, Andriëtte$$tInnovations in Multivariate Statistical Modeling$$dCham : Springer International Publishing AG,c2023$$z9783031139703
001451965 830_0 $$aEmerging topics in statistics and biostatistics.
001451965 852__ $$bebk
001451965 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-13971-0$$zOnline Access$$91397441.1
001451965 909CO $$ooai:library.usi.edu:1451965$$pGLOBAL_SET
001451965 980__ $$aBIB
001451965 980__ $$aEBOOK
001451965 982__ $$aEbook
001451965 983__ $$aOnline
001451965 994__ $$a92$$bISE