Mathematical Statistics and Nonparametric Inference
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D1: Probability and Statistics".
Deadline for manuscript submissions: 20 July 2025 | Viewed by 1162
Special Issue Editors
Interests: semi/nonparametric models; mathematical statistics; change-point(s) detection; spatial and spatial–temporal analysis; functional data analysis
Interests: Bayesian statistics; financial econometrics; interval estimation and hypothesis testing; nonparametric inference; regularization
Special Issues, Collections and Topics in MDPI journals
Interests: multivariate analysis; nonparametric statistics; permutation tests; composite indicators
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are excited to invite you to explore and contribute to our Special Issue on Mathematical Statistics and Nonparametric Estimation. This Special Issue is a platform for sharing cutting-edge research and insights on the latest advancements in mathematical statistics and nonparametric techniques and their real-world applications. It focuses on advancements and applications in statistical theory and methodology, emphasizing nonparametric estimation techniques. Nonparametric methods, essential for analyzing data without assuming specific parametric forms, have gained prominence in diverse fields including environmental science, biostatistics, and finance. Contributions will cover both theoretical developments and applied case studies that demonstrate how nonparametric methods offer flexibility and robustness in analyzing complex data structures. Topics of interest include, but are not limited to, innovative estimation techniques, new models for large datasets, change-point detection, and statistical approaches for high-dimensional data. The Special Issue welcomes original research articles, review papers, and methodological contributions that provide new insights or innovative solutions.
Whether you are a researcher, practitioner, or student, we hope this Special Issue will inspire new ideas and foster collaboration within the statistical community. We look forward to your contributions and hope you enjoy the wealth of knowledge presented here.
Warm regards,
Dr. Hamdy F.F. Mahmoud
Prof. Dr. Jiancheng Jiang
Dr. Stefano Bonnini
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- nonparametric estimation
- mathematical statistics
- change-point detection
- high-dimensional data
- kernel methods
- semiparametric models
- density estimation
- Bayesian nonparametrics
- hypothesis testing
- computational statistics
- stochastic process
- Bayesian probability
- Bernoulli
- Binomial distribution
- Central limit
- Chung–Erdős inequality
- Circular Law
- Branching Process
- Conditional probability
- convergence for sparse
- Convergence in probability
- Convergence of Probability
- Convergence to the limit
- Covariance matrix
- Cumulative distribution function
- diffusion process
- uniform distribution
- Distribution of Sum
- limit of distribution
- limit theorem
- limits of random variables
- Lindeberg's condition
- Littlewood's law
- markov process
- Markovian process
- Markov's inequality
- Maximum likelihood
- negative binomial distribution
- nonparametric statistical
- Pairwise independence
- Paley–Zygmund inequality
- Poisson distribution
- Poisson limit distribution
- Poisson process
- Probability axioms
- probability distribution
- probability theory
- Queueing theory
- random matrices
- random process
- random variable
- random walk
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