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Scale invariant and efficient estimation for groupwise scaled envelope model
Motivated by different groups containing different group information under the heteroscedastic error structure, we propose the groupwise scaled...
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Quasi-maximum likelihood estimation of long-memory linear processes
The purpose of this paper is to study the convergence of the quasi-maximum likelihood (QML) estimator for long memory linear processes. We first...
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Statistical inference of pth-order generalized binomial autoregressive model
To capture the higher-order autocorrelation structure for finite-range integer-valued time series of counts, and to consider the interdependence...
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SurvdigitizeR: an algorithm for automated survival curve digitization
BackgroundDecision analytic models and meta-analyses often rely on survival probabilities that are digitized from published Kaplan–Meier (KM) curves....
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A compartmental model for smoking dynamics in Italy: a pipeline for inference, validation, and forecasting under hypothetical scenarios
We propose a compartmental model for investigating smoking dynamics in an Italian region (Tuscany). Calibrating the model on local data from 1993 to...
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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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Flexible Clustering with a Sparse Mixture of Generalized Hyperbolic Distributions
Robust clustering of high-dimensional data is an important topic because clusters in real datasets are often heavy-tailed and/or asymmetric....
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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...
