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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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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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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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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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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 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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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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Cluster Validation Based on Fisher’s Linear Discriminant Analysis
Cluster analysis aims to find meaningful groups, called clusters, in data. The objects within a cluster should be similar to each other and...
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Forecasting multidimensional autoregressive time series model with symmetric \(\alpha\)-stable noise using artificial neural networks
Artificial neural networks have been widely studied and applied in time series forecasting. However, the existing studies focus more on the...
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DOLD: a digital platform for conducting online language experiments and surveys
Despite its potential for reducing costs, increasing efficiency, and expanding participant diversity, online data collection has not been widely...
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Two-Part Mixed Effects Mixture Model for Zero-Inflated Longitudinal Compositional Data
Compositional data (CD) is mostly analyzed using ratios of components and log-ratio transformations to apply known multivariable statistical methods....
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A New Regression Model for Over-Dispersed Count Responses Based on Poisson and Geometric Convolution
This article presents an alternative generalized linear regression model specifically designed for count responses that exhibit over-dispersion. The...
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Family of Generalized Symmetric Distributions: Properties and Applications
Generalized distributions are useful for applied statisticians, and some of the popular distributions can be extended in several ways. In this study,...
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Optimizing Robust Shape Parameter: Improved Methodologies for Birnbaum–Saunders Distribution
This study strives to improve the estimation of robust estimator when dealing with a univariate Birnbaum–Saunders distribution’s shape parameter...
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Change Point Detection in Length-Biased Weibull Distribution for Random Censored Data Based on Modified Information Criterion
In this article, we study the change point problem of length-biased Weibull distribution under the scenario of random censorship. We construct the...
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A New Look at the Dirichlet Distribution: Robustness, Clustering, and Both Together
Compositional data have peculiar characteristics that pose significant challenges to traditional statistical methods and models. Within this...
