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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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Additive partial linear models with autoregressive symmetric errors and its application to the hospitalizations for respiratory diseases
Additive partial linear models with symmetric autoregressive errors of order p are proposed in this paper for modeling time series data....
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Profile quasi-maximum likelihood estimation for semiparametric varying-coefficient spatial autoregressive panel models with fixed effects
This paper aims to propose a profile quasi-maximum likelihood estimation method for semiparametric varying-coefficient spatial autoregressive(SVCSAR)...
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A spatio-temporal model for binary data and its application in analyzing the direction of COVID-19 spread
It is often of primary interest to analyze and forecast the levels of a continuous phenomenon as a categorical variable. In this paper, we propose a...
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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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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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Inference on Weibull inverted exponential distribution under progressive first-failure censoring with constant-stress partially accelerated life test
Accelerated life tests (ALTs) play a pivotal role in life testing experiments as they significantly reduce costs and testing time. Hence, this paper...
