Statistical Paradigms: Recent Advances and Reconciliations

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:

• Reviews:
  • Weak Paradoxes and Paradigms (Jayanta K Ghosh)
  • Nonparametrics in Modern Interdisciplinary Research: Some Perspectives and Prospectives (Pranab K Sen)
• Parametric:
  • Bounds on Distributions Involving Partial, Marginal and Conditional Information: The Consequences of Incomplete Prior Specification (Barry C Arnold)
  • Stepdown Procedures Controlling a Generalized False Discovery Rate (Wenge Guo and Sanat K Sarkar)
  • On Confidence Intervals for Expected Response in 2ⁿ Factorial Experiments with Exponentially Distributed Response Variables (H V Kulkarni and S C Patil)
  • Predictive Influence of Variables in a Linear Regression Model when the Moment Matrix is Singular (Md Nurul Haque Mollah and S K Bhattacharjee)
  • New Wrapped Distributions — Goodness of Fit (A V Dattatreya Rao, I Ramabhadra Sarma and S V S Girija)
• Semi-Parametric:
  • Non-Stationary Samples and Meta-Distribution (Dominique Guégan)
  • MDL Model Selection Criterion for Mixed Models with an Application to Spline Smoothing (Antti Liski and Erkki P Liski)
  • Digital Governance and Hotspot Geoinformatics with Continuous Fractional Response (G P Patil, S W Joshi and R E Koli)
  • Bayesian Curve Registration of Functional Data (Z Zhong, A Majumdar and R L Eubank)
• Non-Parametric&Probability:
  • Nonparametric Estimation in a One-Way Error Component Model: A Monte Carlo Analysis (Daniel J Henderson and Aman Ullah)
  • GERT Analysis of Consecutive-k Systems: An Overview (Kanwar Sen, Manju Agarwal and Pooja Mohan)
  • Moment Bounds for Strong-Mixing Processes with Applications (Ratan Dasgupta)

Readership: Researchers, professionals and advanced students working on Bayesian and frequentist approaches to statistical modeling and on interfaces for both theory and applications.
Key Features:

• A scholarly and motivating review of non-parametric methods by P K Sen, winner of the Wilks Medal in 2010
• Discussion of paradoxes of the frequentist and Bayesian paradigms, related counterexamples, and their implications
• Stands out in terms of the width and depth