Statistical Inference and Reliability Evaluation of the Perks Distribution under Unified Hybrid Censoring: Applications to Carbon-Fiber Gauge Data
In this paper, we develop statistical inference procedures for the Perks distribution under the Unified Hybrid Censoring Scheme (UHCS). Parameter estimation is performed using several methods, including maximum likelihood estimation (MLE), maximum product of spacings (MPS), and Bayesian estimation via Markov Chain Monte Carlo (MCMC). We derive point and interval estimators and evaluate their performance […]
Nagarjuna Distribution: A Transformed Bounded Weibull Model with Bathtub Risk Function and Applications
This study introduces a new flexible bounded model on the unit-interval (0,1) obtained through a nonlinear transformation of the Weibull distribution called the Nagarjuna distribution. The flexibility of the proposed distribution allows it to accommodate different shapes, including symmetric, skewed, U-shaped, decreasing density forms and other new types forms, along with various risk function behaviors, […]
Improved Inference for the Arz Distribution: A Comparative Analysis of Confidence Intervals with Applications
This study develops and evaluates four distinct methods for constructing confidence intervals (CIs) for the parameter of the Arz distribution—a model newly employed in the analysis of lifetime data. The examined CI methods include the likelihood-based CI, the Wald-type CI, the bootstrap-t CI, and the bias-corrected and accelerated (BCa) bootstrap CI. To assess the performance […]
Modified group chain acceptance sampling plans for lifetimes based on the compound Marshall-Olkin-Weibull distribution
In this paper, a modified group chain acceptance sampling plan is developed based on truncated lifetimes when the life times of items follow a new kind of compound Marshall Olkin-Weibull distribution. The unknown design parameters values, i.e., optimal number of groups, operating characteristic values and optimal mean ratio of this plan are calculated by satisfying […]
Dynamics of rabies transmission: A fractional-order approach via stability, bifurcation, and optimal control theory
Rabies remains a critical zoonotic threat characterized by complex transmission dynamics between domestic dogs and human populations. Despite its severity, traditional integer-order models often overlook the hereditary properties and non-local memory effects inherent in epidemiological spread, necessitating more robust mathematical frameworks. To address this, this study presents a fractional-order mathematical model for simulating the nonlinear […]
Reliability estimation of inverse Chen model using constant-stress accelerated life tests
Accelerated life testing provides an effective approach for assessing product reliability within a shorter time by exposing test units to higher levels of stress than those experienced under normal operating conditions. This study considers a constant-stress testing plan, in which each product is subjected to a fixed level of stress throughout the entire experiment. The […]
The New Marshall-Olkin Type II Exponentiated Half Logistic-Gompertz-G Family of Distributions: Properties and Applications
In this work, a new family of distributions referred to as Marshall-Olkin type II exponentiated half logistic-Gompertz-G distribution is introduced and studied. Some statistical properties including hazard rate and quantile functions, series expansion of the density function, moments, order statistics and Rénnyi entropy are derived. Special cases, particularly when the baseline distributions are log-logistic and […]
Mathematical Modeling of Brain Diseases: A Bibliometric Review
Brain diseases significantly affect the brain’s structure and function, impacting an individual’s sense of self, autonomy, and physical abilities. They are increasingly common due to stressful lifestyles and are a major global health issue. Research into brain structure and function is essential for understanding health and illness. Due to the brain’s complexity, mathematical modeling is […]
XGBoost algorithm for a spatial point process intensity estimation based on logistic loss
Spatial point processes provide a framework for modeling the spatial distribution of events. Practice dictates that when the intensity depends on a number of covariates, parametric approaches often play a good role. Alternatively, nonparametric kernel-based estimation is also well established in the literature. However, complex relationships across covariates can make the parametric approaches less efficient, […]
An entropy transformed Weibull extended distribution for real world data analytics
Proliferation of data all over the world requires the development of advance methodologies. These methodologies provide frameworks for the analysis of complex data with a high degree of accuracy. In response to the need for accurate methodologies, this study proposes a new distribution using entropy transformation, called the entropy transformed generalized new extended Weibull distribution. […]