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Asymptotic Results for the Absorption Time of Telegraph Processes with Elastic Boundary at the Origin
We consider a telegraph process with elastic boundary at the origin studied recently in the literature (see e.g. Di Crescenzo et al. (Methodol Comput...
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A Non-local Fokker-Planck Equation with Application to Probabilistic Evaluation of Sediment Replenishment Projects
We analyze a new mathematical model to evaluate performance of recent sediment-based environmental restoration projects from a stochastic viewpoint...
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Degradation and Failure Mechanisms of Complex Systems: Principles
A cyber–physical–human complex system failure prevents the accomplishment of the system’s intended function. The failure of a complex system could be...
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AI-Powered Bayesian Statistics in Biomedicine
Statistics and artificial intelligence (AI) are distinct yet closely interconnected disciplines, each characterized by its own historical roots and...
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Classification of Free-Living Body Posture with ECG Patch Accelerometers: Application to the Multicenter AIDS Cohort Study
As health studies increasingly monitor free-living heart performance via ECG patches with accelerometers, researchers will seek to investigate...
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Stability Analysis for Pricing European Options Regarding the Interest Rate Generated by the Time Fractional Cox-Ingersoll-Ross Processes
In this paper, we introduce a new methodology for pricing European options when the interest rate is generated by the Time Fractional...
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Telegraph Process with Elastic Boundary at the Origin
We investigate the one-dimensional telegraph random process in the presence of an elastic boundary at the origin. This process describes a...
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Sample of Specialized Survey Analyses
There are many specialized analyses for Core Questions. I will summarize a few in this chapter to highlight the possibilities with Python.
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High-dimensional penalized Bernstein support vector classifier
The support vector machine (SVM) is a powerful classifier used for binary classification to improve the prediction accuracy. However, the...
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Discrimination and Classification
IF WE HAVE multivariate observations from two or more identified populations, how can we characterize them? Is there a combination of measurements to...
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Linear Regression
Linear regression relates predictor variables and outcome variables, such as gene copy numbers and the level of a biomarker. The assumed linearity of...
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Shape-based functional data analysis
Functional data analysis (FDA) is a fast-growing area of research and development in statistics. While most FDA literature imposes the classical
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Asymptotic linear expansion of regularized M-estimators
Parametric high-dimensional regression requires regularization terms to get interpretable models. The respective estimators correspond to regularized...
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Penalized polygram regression
We consider a study on regression function estimation over a bounded domain of arbitrary shapes based on triangulation and penalization techniques. A...
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Some Results on the Telegraph Process Confined by Two Non-Standard Boundaries
We analyze the one-dimensional telegraph random process confined by two boundaries, 0 and H > 0. The process experiences hard reflection at the...
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A Generalized Quadratic Garrote Approach Towards Ridge Regression Analysis
Ridge regression is widely used in multiple linear regression analysis to address the prevalent multicollinearity issue in high-dimensional settings....
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A Riemannian geometric framework for manifold learning of non-Euclidean data
A growing number of problems in data analysis and classification involve data that are non-Euclidean. For such problems, a naive application of...
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Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset
This paper tackles the challenge presented by small-data to the task of Bayesian inference. A novel methodology, based on manifold learning and...
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Penalized and constrained LAD estimation in fixed and high dimension
Recently, many literatures have proved that prior information and structure in many application fields can be formulated as constraints on regression...
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Flexible Conditional Borrowing Approaches for Leveraging Historical Data in the Bayesian Design of Superiority Trials
In this paper, we consider the Bayesian design of a randomized, double-blind, placebo-controlled superiority clinical trial. To leverage multiple...
