Most Cited

This study aimed to perform a bibliometric analysis of terroir and explore its conceptual horizons. Advancements in terroir research until 2022 were investigated using the Scopus database, R, and VOSviewer. Out of the 907 results, the most prevalent...

In this paper, we propose a weighted Lindley (NWLi) model for the analysis of extreme historical insurance claims. It extends the classical Lindley distribution by incorporating a weight parameter, enabling more flexibility in modeling insurance clai...

Owing to the development of the technologies of Industry 4.0, recent years have witnessed the emergence of a new concept of supply chain management, namely Supply Chain 4.0 (SC 4.0). Huge investments in information technology have enabled manufacture...

The COVID-19 outbreak has rapidly affected global economies and the parties involved. There was a need to ensure the sustainability of corporate finance and avoid bankruptcy. The reactions of individuals were not routine, but covered a wide range of...

The new Ristić and Balakhrisnan or Gamma-Topp-Leone-Type II-Exponentiated Half Logistic-G (RB-TL-TII-EHL-G) family of distributions is introduced and investigated in this paper. This work derives and studies some of the main statistical characte...

Factor analysis, a staple of correlational psychology, faces challenges with ordinal variables like Likert scales. The validity of traditional methods, particularly maximum likelihood (ML), is debated. Newer approaches, like using polychoric correlat...

The two-parameter logistic (2PL) item response theory model is a statistical model for analyzing multivariate binary data. In this article, two groups are brought onto a common metric using the 2PL model using linking methods. The linking methods of...

In this study, we introduce a new generalized family of distributions called the Exponentiated Half Logistic-Harris-G (EHL-Harris-G) distribution, which extends the Harris-G distribution. The motivation for introducing this generalized family of dist...

Change-point detection is a challenging problem that has a number of applications across various real-world domains. The primary objective of CPD is to identify specific time points where the underlying system undergoes transitions between different...

Ensemble learning (EL) has become an essential technique in machine learning that can significantly enhance the predictive performance of basic models, but it also comes with an increased cost of computation. The primary goal of the proposed approach...

Researchers interested in the assessment of substance use trajectories, and predictors of change, have several data analysis options. These include, among others, generalized estimating equations and latent growth curve modeling. One difficulty in th...

This paper explores international tourism regarding Morocco’s leading touristic city Marrakech, and, more precisely, its two prominent public spaces, Jemaa el-Fna and the Medina. Following a web-scraping process of English reviews on TripAdviso...

Incident clearance time (ICT) is impacted by several factors, including crash injury severity. The strategy of most transportation agencies is to allocate more resources and respond promptly when injuries are reported. Such a strategy should result i...

Clinical trials often collect intermediate or surrogate endpoints other than their true endpoint of interest. It is important that the treatment effect on the surrogate endpoint accurately predicts the treatment effect on the true endpoint. There are...

Patent keyword analysis is used to analyze the technology keywords extracted from collected patent documents for specific technological fields. Thus, various methods related to this type of analysis have been researched in the industrial engineering...

The goal of this study is to detect linear and nonlinear causal pathways toward climate change as measured by changes in global mean surface temperature and global mean sea level over time using a data-based approach in contrast to the traditional ph...

Coopetition means that in economic interactions, both competition and cooperation are presented in the same time. We built and investigated analytically and numerically game theoretic models of coopetition in normal form and in the form of characteri...

Structural equation models constrain mean vectors and covariance matrices and are frequently applied in the social sciences. Frequently, the structural equation model is misspecified to some extent. In many cases, researchers nevertheless intend to w...

Shannon’s entropy is a fundamental concept in information theory that quantifies the uncertainty or information in a random variable or data set. This article addresses the estimation of Shannon’s entropy for the Maxwell lifetime model ba...

We define and study the four-parameter logistic Burr XII distribution. It is obtained by inserting the three-parameter Burr XII distribution as the baseline in the logistic-X family and may be a useful alternative method to model income distribution...

In social sciences, multiple groups, such as countries, are frequently compared regarding a construct that is assessed using a number of items administered in a questionnaire. The corresponding scale is assessed with a unidimensional factor model inv...

Imputing missing values in high-dimensional time-series data remains a significant challenge in statistics and machine learning. Although various methods have been proposed in recent years, many struggle with limitations and reduced accuracy, particu...

The lack of data on flood events poses challenges in flood management. In this paper, we propose a novel approach to enhance flood-forecasting models by utilizing the capabilities of Generative Adversarial Networks (GANs) to generate synthetic flood...

A new unimodal distribution family indexed via the mode and three other parameters is derived from a mixture of a Gumbel distribution for the maximum and a Gumbel distribution for the minimum. Properties of the proposed distribution are explored, inc...

Fractional Stochastic Differential Equations are becoming more popular in the literature as they can model phenomena in financial data that typical Stochastic Differential Equations models cannot. In the formulation considered here, the Hurst paramet...

The Weibull is a popular distribution that models monotonous failure rate data. In this work, we introduce the four-parameter Weibull extended Weibull distribution that presents greater flexibility, thus modeling data with bathtub-shaped and unimodal...

Researchers conducting longitudinal data analysis in psychology and the behavioral sciences have several statistical methods to choose from, most of which either require specialized software to conduct or advanced knowledge of statistical methods to...

In the present paper, a new special function, the so-called extreme value $\mathbb{H}$-function, is introduced. This new function, which is a generalization of the H-function with a particular set of parameters, appears while dealing with products and quotients...

Based upon the vector representation of complex numbers and the vector exponential function, we introduce the vector representation of characteristic functions and consider some of its elementary properties such as its polar representation and a vect...

While many studies have previously conducted direct comparisons between results obtained from frequentist and Bayesian models, our research introduces a novel perspective by examining these models in the context of a small dataset comprising phonetic...

Reference intervals play an important role in medicine, for instance, for the interpretation of blood test results. They are defined as the central 95% values of a healthy population and are often stratified by sex and age. In recent years, so-called...

The rise of explainable natural language processing spurred a bulk of work on datasets augmented with human explanations, as well as technical approaches to leverage them. Notably, generative large language models offer new possibilities, as they can...

By collecting and expanding several numerical recipes developed in previous work, we implement an object-oriented Python code, based on the networkX library, for the realization of the configuration model and Newman rewiring. The software can be appl...

In multifactor fixed-effects ANOVAs, we show how to construct orthonormal F contrasts for main effects. Our primary focus is the case when the levels of the factor of interest are ordered. Likewise, in multifactor equally replicated fixed-effects ANO...

This paper studies a subclass of the class of generalized hyperbolic distribution called the semi-hyperbolic distribution. We obtain analytical expressions for the cumulative distribution function and, specifically, their first and second lower parti...

We use an extended framework of the technology acceptance model (TAM) to identify the most significant drivers behind the intention to buy clothes produced with nano fabrics (nano clothing). Based on survey data, we estimate an integrated model that...

This work presents a brief review on the modern approaches to data modeling by the methods developed in the quantum physics during the last one hundred years. Quantum computers and computations have already been widely investigated theoretically and...

Reliability allocation is the process of assigning reliability targets to sub-systems within a system to meet the overall reliability requirements. However, many traditional reliability allocation methods rely on assumptions that are often unrealisti...

We propose an unbiased restricted estimator that leverages prior information to enhance estimation efficiency for the linear regression model. The statistical properties of the proposed estimator are rigorously examined, highlighting its superiority...

A new family of inequality indices based on the deviation between the expected maximum and the expected minimum of random samples, called the nth Gini index is presented. These indices generalize the Gini index. At the same time, this family of indic...

For decades, conventional wisdom maintained that binary 0–1 Bernoulli random variables cannot contain extra-binomial variation. Taking an unorthodox stance, Hilbe actively disagreed, especially for correlated observation instances, arguing that...

Methodological experts suggest that psychological and educational researchers should employ appropriate methods for data-driven model exploration, such as Bayesian Model Averaging and regularized regression, instead of conventional hypothesis-driven...

Nonprobability samples have been used frequently in practice including public health study, economics, education, and political polls. Naïve estimates based on nonprobability samples without any further adjustments may suffer from serious select...

Although large data sets are generally viewed as advantageous for their ability to provide more precise and reliable evidence, it is often overlooked that these benefits are contingent upon certain conditions being met. The primary condition is the a...

Only a few count smoothers are available for the widespread use of discrete associated kernel estimators, and their constructions lack systematic approaches. This paper proposes the mean dispersion technique for building count kernels. It is only app...

The usual method of separating signal and noise principal components on the sole basis of their eigenvalues has evident drawbacks when semantically relevant information ‘hides’ in minor components, explaining a very small part of the tota...

The time-between-events idea is commonly used for monitoring high-quality processes. This study aims to monitor the increase and/or decrease in the process mean rapidly using a one-sided exponentially weighted moving average (EWMA) chart for the dete...

It is evident that several real-life applications, such as telecommunication systems, call for the establishment of consecutive-type networks. Moreover, some of them require more complex connectors than the ones that exist already in the literature....

The dominance of non- and semi-parametric methods in survival analysis is not without criticism. Several studies have highlighted the decrease in efficiency compared to parametric methods. We revisit the problem of Asymptotic Relative Efficiency ($ARE$...

This paper considers the construction of a family of discrete distributions with the flexibility to cater for under-, equi- and over-dispersion in count data using a finite mixture model based on standard distributions. We are motivated to introduce...