Nonparametric Statistical Methods and Their Applications

Dear Colleagues,

You are kindly invited to contribute to this Special Issue on “Nonparametric Statistical Methods and Their Applications” with an original research paper or a comprehensive review. The main focus is on new theoretical proposals, applications and/or computational aspects of nonparametric statistical methods. The papers should cover a wide spectrum of topics concerning nonparametric and semiparametric methods for inferential or exploratory data analysis. The methodological topics of interest include but are not limited to:

• Rank tests
• Permutation tests
• Goodness-of-fit tests
• Bootstrap methods
• Nonparametric curve and/or density estimation
• Regression smoothing
• Symmetry testing
• Robust estimation
• Nonparametric filtering
• Ranked set sampling
• Bayesian nonparametrics
• Semiparametric models and procedures

Many statistical methods are often based on assumptions that cannot be tested, are not plausible or are not justified by asymptotic theories (e.g., with small sample sizes). For these reasons, nonparametric statistical methods have become increasingly important and widespread in several empirical disciplines. A non-exhaustive list of the application-based areas of interest for the Special Issue is as follows: psychology, business and economics, finance, economic and social sciences, biomedical sciences, engineering, chemistry, environmental sciences, quality evaluation, multicriteria decision making, big data, DOE, computer science, computational intelligence, and machine learning.  

Prof. Dr. Stefano Bonnini
Guest Editor

Manuscript Submission Information

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