Titlebook: Innovations in Multivariate Statistical Modeling; Navigating Theoretic Andri?tte Bekker,Johannes T. Ferreira,Ding-Geng Ch Book 2022 The Edi

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A Flexible Matrix-Valued Response Regression for?Skewed Datapplications, outliers usually contaminate matrix-valued data. This chapter introduces a new flexible family of matrix-variate distributions that includes the matrix normal distribution as a particular member. By considering the introduced distribution for the error term, we develop a regression mode

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Multivariate Functional Singular Spectrum Analysis: A Nonparametric Approach for Analyzing Multivari a multivariate functional time series (MFTS) into interpretable partitions such as mean, periodic, and trend components. The approach is flexible in the sense that the MFTS signal may be composed of functional observations such as curves and surfaces and the offered flexibility can lead to richer s

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Multivariate Count Data Regression Models and Their Applications some distributions generated from the .-.{.} method will be defined. Models that allow both positive and negative correlation between any pair of response variables will be considered. The model parameters will be estimated by using the method of maximum likelihood estimation. The application of th

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A Generalized Quadratic Garrote Approach Towards Ridge Regression AnalysisIn the standard form of ridge regression analysis, all model coefficients are shrunken towards zero at a similar rate regardless of the importance of each variable. In this paper, we provide an extension of the non-negative garrote method to give more flexibility to the ridge regression approach for

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