The xgamma distribution was first introduced by Sen et al. [1] as an alternative distribution to the exponential model. The xgamma distribution exhibits a bathtub-shaped hazard rate function, so it is suitable for many lifetime phenomena. In this …

Recognizing and reducing risk is a major part of Supply Chain Management (SCM). Several companies are invested in Supply Chain Risk Management (SCRM) and they have the knowledge about the procurement occupancies within their companies and take …

One of the key objectives of statistics is to provide a model compatible with the data generated by an unknown random process. Often, it happens that the unknown process is intractable, and no prior data or information associated with the unknown …

We live in a world where everything is connected to online social media platforms, and the person uses social media networks like Face book, Twitter, Instagram, Whatsapp, etc. In the present scenario, working women, celebrities, sports persons …

The advancement of technology has increased competitiveness, especially in the manufacturing industry. Alongside Statistical Process Control (SPC), capacity indices are tools used to measure the quality of processes and are useful for establishing …

Two known characteristics of the distribution of stock returns (price fluctuations) and, more recently, the distribution of financial asset volumes are power laws and scaling. These power laws can be viewed as the asymptotic behaviour of …

In light of the rapid technological advancements witnessed in recent decades, numerous disciplines have been inundated with voluminous datasets characterized by multimodality, heavy-tailed distributions, and prevalent missing information.

Data science often employs discrete probability distributions to model and analyze various phenomena. These distributions are particularly useful when dealing with data that can be categorized into distinct outcomes or events. This study presents …

The rise of mobile technology has significantly transformed numerous aspects of our everyday lives, especially within food delivery services. The investigation aims to explore the food delivery mobile apps (FDMA) satisfaction (SAT) and the …

This paper has investigated an empirical study to consider the impact of supply chain management on small scale integrated commercial agriculture by focusing on the moderator role of impediments and obligations to offer solutions for agricultural …

This paper introduces a Modified Lindley distribution using a convex combination of exponential and gamma distribution. The fundamental properties of the proposed distribution such as the shapes of the distribution, moments, mean, variance …

Hyperspectral image classification involves assigning pixels or regions within a hyperspectral image to specific classes or categories based on the spectral information captured across multiple bands. Traditional method faces several challenges …

This paper presents a novel nonlinear binary classification method, namely the kernel-free reduced quadratic surface support vector machine with 0-1 loss function and L $$_{p}$$ p -norm regularization (L $$_p$$ p -RQSSVM $$_{0/1}$$ 0 / 1 ). It …

Nature-inspired algorithms (NIA) are proven to be the potential tool for solving intricate optimization problems and aid in the development of better computational techniques. In recent years, these algorithms have raised considerable interest to …

Advancements in genome sequencing technologies have significantly increased the availability of genomic data. The use of machine learning models to predict the pathogenicity or clinical significance of genetic mutations is crucial. However …

Developing effective methodologies for territory design and relativity estimation is crucial in auto insurance rate filings and reviews. This study introduces a novel approach utilizing fuzzy clustering to enhance the design process of territories …

Carbon emissions disclosure (CED) has become a pivotal aspect of corporate sustainability efforts, reflecting a company’s commitment to environmental responsibility and accountability. This study delves into the complex connection between CED and …

Partial label learning (PLL) is a particular problem setting within weakly supervised learning. In PLL, each sample corresponds to a candidate label set in which only one label is true. However, in some practical application scenarios, the …

In this paper, a nonparametric kernel method is introduced to estimate the well-known overlapping coefficient, Matusita $$\rho (X,Y)$$ ρ ( X , Y ) , between two random variables $$X$$ X and $$Y$$ Y . Due to the complexity of finding the formula …

In this paper we first define the class of Generalized Inflated Power Series Distributions (GIPSDs) which contain the inflated discrete distributions most often seen in practice as special cases. We describe the hitherto unkown exponential family …