Latent Gaussian Approach to Joint Modelling of Longitudinal and Mixture Cure Outcomes
Joint modelling has become pervasive in analysing data from survival and longitudinal studies. There are several technqiues on joint analyses of datasets from both studies simultaneously. Our interest here is on approximate Bayesian inference using latent Gaussian models (LGMs) to analyse longitudinal and mixture cure outcomes with shared random effect. Longitudinal outcome was modelled using […]
Point and Interval Estimation of Reliability and Entropy for Generalized Exponential Distribution under Generalized Type-II Hybrid Censoring Scheme
In this research paper, the estimation of reliability and entropy measures are analyzed within the context of a generalized Type-II hybrid censoring scheme (GT2HCS) The analysis is conducted while considering a generalized exponential distribution as the underlying lifetime distribution. The study specifically emphasizes the calculation of both Shannon and Renyi entropy measures. Maximum likelihood estimation […]
Leveraging Data Mining for Inference and Prediction in Lung Cancer Research
Lung cancer~is the second most common cancer worldwide, with an estimated 2.21 million new diagnoses and 1.8 million deaths in 2020, according to WHO. Successful lung cancer treatment, early detection, and diagnosis improve survival rates. This study included 270 lung cancer patients and 39 with no lung cancer patients. Logistic regression will be used to […]
Statistical Analysis of Inverse Weibull based on Step-Stress Partially Accelerated Life Tests with Unified Hybrid Censoring Data
Accelerated life testing (ALT) is a primary method for rapidly evaluating product reliability. This paper focuses on statistical inference for the invertedWeibull distribution under a step-stress partially ALT (SSPALT) model with a unified hybrid censoring scheme. This censoring scheme enhances the efficiency of statistical analysis and reduces overall test time. The inverted Weibull distribution is […]
Predicting the Trends of the Egyptian Stock Market Using Machine Learning and Deep Learning Methods
The prediction of stock price movements has remained a significant area of interest for researchers and investors, driven by the dynamic nature of financial markets and persistent economic fluctuations. The ability to forecast price trends enables investors to optimize their portfolios by identifying stocks likely to appreciate in value while avoiding those predicted to decline, […]
Statistical Properties and Applications of a New Truncated Zubair- Generalized Family of Distributions
This paper proposed a truncated family of probability distributions named the doubly truncated Zubair-generalized family of truncated distributions. Certain properties of doubly truncated Zubair-Generalized family of truncated distributions are worked on. These properties are the quantile, median, the non-central moments, central moments, order statistics, entropy measures such as R$\acute{e}$nyi, Shannon, Tsallis entropies, also the mean […]
A New Logarithmic Tangent-U Family of Distributions with Reliability Analysis in Engineering Data
This article introduces a new family of distributions through the transformation involving tangent functions, referred to as the New Logarithmic Tangent-U family. The newly introduced family may be written as the NLT-U family of distribution. An overview of fundamental characteristics inherent to the proposed family of distributions is provided. We derived a special sub-model of […]
Statistical Analysis of Alpha-Power Exponential Distribution Using Unified Hybrid Censored Data and Its Applications
A new extended exponential distribution called the alpha-power exponential (APE) distribution is widely used for modeling various data compared to three well-known models, namely Weibull, gamma, and generalized-exponential distributions. This paper provides several approaches for estimating the APE parameters, reliability, and hazard rate functions using both classical and Bayesian methods when dealing with unified hybrid […]
A New Biased Estimation Class to Combat the Multicollinearity in Regression Models: Modified Two–Parameter Liu Estimator
The multicollinearity problem occurrence of the explanatory variables affects the least-squares (LS) estimator seriously in the regression models. The multicollinearity adverse effects on the LS estimation are also investigated by many authors. Instead of the LS estimator, we propose a new modified two–parameter Liu (MTPL) estimator to handle the multicollinearity for the regression model based […]
Bayesian and E-Bayesian Estimation of Gompertz Distribution in Stress-Strength Reliability Model under Partially Accelerated Life Testing
A reliability experiment is a crucial determinant of a component’s success, as it simulates the effects of aging and usage by exposing the component in a system to higher levels of stress or wear. Consequently, assessments of the component’s performance and its capacity to satisfy consumers are conducted. This study aims to estimate the stress-strength […]