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基本説明
Consists of a collection of research articles on classical and emerging Statistical Paradigms - parametric, non-parametric and semi-parametric, frequentist and Bayesian - encompassing both theoretical advances and emerging applications in a variety of scientific disciplines.
Full Description
This volume consists of a collection of research articles on classical and emerging Statistical Paradigms — parametric, non-parametric and semi-parametric, frequentist and Bayesian — encompassing both theoretical advances and emerging applications in a variety of scientific disciplines. For advances in theory, the topics include: Bayesian Inference, Directional Data Analysis, Distribution Theory, Econometrics and Multiple Testing Procedures. The areas in emerging applications include: Bioinformatics, Factorial Experiments and Linear Models, Hotspot Geoinformatics and Reliability.
Contents
Weak Paradoxes And Paradigms; Nonparametrics in Modern Interdisciplinary Research: Some Perspectives and Prospectives; Stepdown GERT Analysis of Consecutive-K Systems: An Overview; Bounds on Distributions Involving Partial, Marginal and Conditional Information: The Consequences of Incomplete Prior Specification; New Wrapped Distributions; Non-Stationarity and Meta-Distribution; Moment Bounds for Strong-Mixing Processes with Applications; On Confidence Intervals for Expected Response in 2n Factorial Experiments with Exponentially Distributed Response Variables; Non-parametric Estimation in a One-Way Error Component Model: A Monte-Carlo Analysis; Predictive Influence of Variables in a Linear Regression Model When the Moment Matrix (X'X) is Singular; Bayesian Curve Registration of Functional Data; MDL Modeling Criterion for Linear Mixed Models; Procedures Controlling a Generalized False Discovery Rate; Digital Governance and Hotspot Geoinformatics with Continuous Fractional Response.
