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rendao y skew normal model theories applications 2024

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Textbook in PDF format This book focuses on several skew-normal mixed effects models, and systematically explores the statistical inference theories, methods, and applications of parameters of interest. This book is of academic value, since it helps to establish a series of statistical inference theories and methods for skew-normal mixed effects models. It will also provide efficient methods and tools for practical data analysis in various fields including economics, finance, biology and medical science, which features its application value. Preface Table of Contents Introduction Model outline Research status Skew-normal distribution Bootstrap approach Generalized approach Research methods and ideas Research characteristics and innovation points Research content and frame Preliminary Knowledge Multivariate skew-normal distribution Skew-normal random vector Quadratic form of a skew-normal random vector Distribution of a skew-normal matrix quadratic form Skew-normal random matrix Distribution of a quadratic form Bootstrap approach Bootstrap test Bootstrap confidence interval Generalized p-value and generalized confidence interval Location Parameter of Skew-Normal Population Conditional test statistic Parameter estimation Bootstrap test Monte Carlo simulation Illustrative examples Common Location Parameter of Skew-Normal Populations Parameter estimation Bootstrap confidence interval Monte Carlo simulation Illustrative examples One-Way Classification Model with Skew-Normal Random Effects Model properties Parameter estimation Bootstrap inference of fixed effect Inference on variance component functions Inference on the single variance component Inference on the sum of variance components Inference on the ratio of variance components Monte Carlo simulation Illustrative examples Unbalanced One-Way Classification Model with Skew-Normal Random Effects Model properties Inference on the fixed effect Inference on variance component functions Inference on the single variance component Inference on the sum of variance components Inference on the ratio of variance components Monte Carlo simulation Illustrative example Skew-Normal Unbalanced Heteroscedastic One-Way Classification Random Effects Model Model properties Inference on the fixed effect Inference on the single variance component Bootstrap approach Generalized approach Inference on the sum of variance components Bootstrap approach Generalized approach Inference on the ratio of variance components Bootstrap approach Generalized approach Monte Carlo simulation Illustrative examples Skew-Normal Unbalanced Panel Model with One-Way Error Component Model properties Parameter estimation Inference on the single variance component Bootstrap approach Generalized approach Inference on the sum of variance components Bootstrap approach Generalized approach Inference on the ratio of variance components Monte Carlo simulation Illustrative examples Skew-Normal Two-Way Classification Random Effects Model with Interaction Model properties Inference on the fixed effect Inference on the single variance component Bootstrap approach Generalized approach Inference on the sum of variance components Bootstrap approach Generalized approach Inference on the ratio of variance components Bootstrap approach Generalized approach Monte Carlo simulation Illustrative examples Skew-Normal Mixed Effects Model Skew-normal mixed effect model with two random effects Quadratic form and its Cochran’s theorem Exact inference of unknown parameters Monte Carlo simulation Illustrative example Skew-normal mixed effect model with k+1 random effects Quadratic form and its Cochran’s theorem Exact inference of unknown parameters Monte Carlo simulation Illustrative examples References Index

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rendao y skew normal model theories applications 2024