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Oracle-efficient M-estimation for single-index models with a smooth simultaneous confidence band
Single-index models are important and popular semiparametric models, as they can handle the problem of the “curse of dimensionality” and enjoy the...
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A mixture of experts regression model for functional response with functional covariates
Due to the fast growth of data that are measured on a continuous scale, functional data analysis has undergone many developments in recent years....
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Pediatric injuries and poisonings associated with detergent packets: results from the Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP), 2011–2023
BackgroundDetergent packets are common household products; however, they pose a risk of injuries and poisonings, especially among children. This...
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An evaluation of sample size requirements for develo** risk prediction models with binary outcomes
BackgroundRisk prediction models are routinely used to assist in clinical decision making. A small sample size for model development can compromise...
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Multivariate Leimkuhler Curve: Properties and Applications to Analysis of Bibliometric Data
The Leimkuhler curve has established itself as an efficient tool in the analysis and comparison of concentration of bibliometric measures of...
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Estimation and backtesting of risk measures with emphasis on distortion risk measures
Statistical methodology has an important role to play in risk measurement. In this paper, we will review and discuss some statistical issues on risk...
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A limit formula and a series expansion for the bivariate Normal tail probability
This work presents a limit formula for the bivariate Normal tail probability. It only requires the larger threshold to grow indefinitely, but...
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Strong convergence of a nonparametric relative error regression estimator under missing data with functional predictors
In this paper, we develop a nonparametric estimator of the regression function for a functional explanatory variable and a scalar response variable...
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Classifier-dependent feature selection via greedy methods
The purpose of this study is to introduce a new approach to feature ranking for classification tasks, called in what follows greedy feature...
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Clustering with Minimum Spanning Trees: How Good Can It Be?
Minimum spanning trees (MSTs) provide a convenient representation of datasets in numerous pattern recognition activities. Moreover, they are...
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A Note on Ising Network Analysis with Missing Data
The Ising model has become a popular psychometric model for analyzing item response data. The statistical inference of the Ising model is typically...
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Locally sparse and robust partial least squares in scalar-on-function regression
We present a novel approach for estimating a scalar-on-function regression model, leveraging a functional partial least squares methodology. Our...
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A New Matrix Feature Selection Strategy in Machine Learning Models for Certain Krylov Solver Prediction
Numerical simulation processes in scientific and engineering applications require efficient solutions of large sparse linear systems, and variants of...
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A Personal Celebration of Dr. D. Basu with Emphasis on Examples-Counterexamples-Clarifications
Preparing this centennial tribute to Dr. D. Basu (5 July, 1924 – 24 March, 2001) created an opportunity to selectively revisit a number of core...
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New Paradigm of Identifiable General-response Cognitive Diagnostic Models: Beyond Categorical Data
Cognitive diagnostic models (CDMs) are a popular family of discrete latent variable models that model students’ mastery or deficiency of multiple...
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Binary classification with fuzzy logistic regression under class imbalance and complete separation in clinical studies
BackgroundIn binary classification for clinical studies, an imbalanced distribution of cases to classes and an extreme association level between the...
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Scalable Bayesian p-generalized probit and logistic regression
The logit and probit link functions are arguably the two most common choices for binary regression models. Many studies have extended the choice of...
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On weak convergence of quantile-based empirical likelihood process for ROC curves
The empirical likelihood (EL) method possesses desirable qualities such as automatically determining confidence regions and circumventing the need...
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Automating incidence and prevalence analysis in open cohorts
MotivationData is increasingly used for improvement and research in public health, especially administrative data such as that collected in...