A Bayesian approach to survival analysis of COVID-19 data using the additive flexible Weibull extension-Lomax distribution
This study investigates the Bayesian estimation for the additive flexible Weibull extension-Lomax (AFWE-L) distribution, a versatile model designed to capture complex survival data patterns. Using Type II censored samples and a joint bivariate informative prior, Bayes estimators are derived for the distribution’s unknown model parameters, reliability metrics such as the hazard and reversed hazard rate […]
Using machine learning models with elephant herd feature selection method for diagnosing chronic kidney disease
The kidneys filter waste, toxins, and excess water from the bloodstream, promoting body balance. Chronic kidney disease (CKD) is defined as a progressive deterioration of kidney function. Chronic kidney disease is a serious health condition that affects people all over the world. Early detection of kidney disease is crucial due to the lack of visible […]
Advancing lifetime data modeling via the Marshall-Olkin cosine Topp-Leone distribution family
Probability distributions are fundamental tools in statistical modeling, particularly in the analysis of lifetime, reliability, and epidemiological data. Classical distributions such as the exponential, Weibull, and gamma, while analytically convenient, often lack the flexibility required to model complex real-world phenomena, such as skewness, heavy tails, and intricate dependence structures. In response to these limitations, this […]
Unsupervised feature selection via fuzzy c-means clustering and binary atom search algorithm
This paper presents a proposed algorithm that combines the Binary Atomic Search (BAS) algorithm and the Fuzzy C-means Method (FCM) technique, called BAS-FCM. The proposed algorithm, BAS-FCM, is based on two-stage data processing. The first stage involves selecting important features from the datasets and discarding unimportant ones using the BAS algorithm, which relies on a […]
A new probability continuous distribution with different estimation methods and application
The inverse Ramos-Louzada distribution (IRLD), a novel one-parameter distribution designed to handle real data with hazard rates shaped like an upside-down bathtub, is presented in this work. The IRLD can be used for many applications and has asymmetric and unimodal density shapes. We derive some of the IRLD’s main statistical characteristics, such as moments, incomplete […]
Characterization of Some Probability Distributions Based on Conditional Expectation and Variance
The characterizations of probability distributions have been studied by several academics. When a certain distribution is the only one that correlates with a given property, a characterization theorem in probability and statistics is applicable. Additionally, a characterization is a particular distributional or statistical property of a statistic or statistics that describes the corresponding stochastic model […]
Statistical Inference for the Marshall-Olkin Extended Modified Inverse Rayleigh Distribution Under Adaptive Type-II Progressive Censoring
The Marshall-Olkin extended modified inverse Rayleigh (MOEMIR) distribution, a new extension of the modified inverse Rayleigh} (MIR) distribution, is introduced as a member of a proposed \textit{Marshall-Olkin extended general inverse exponential (MOEGIE) family. This extension offers enhanced flexibility for modeling lifetime data. Statistical properties of the MOEGIE family are presented, and hence those of the […]
Autoregressive moving-average time series model with errors following a log-logistic distribution
In the class of time series’ models, the errors of the fitted models may follow a Log-Logistic distribution instead of the Normal distribution. This new model is called the Log-Logistic Autoregressive Moving-Average(L-LARMA) model. Following the introduction of this model’s structure, its parameters have been estimated using numerical methods and the conditional maximum likelihood function. The […]
A Discrete expansion of the Lindley distribution: Mathematical and statistical characterizations with estimation techniques, simulation, and goodness-of-fit analysis
The objective of this paper is to introduce the discretized two-parameter Lindley (D2PL) distribution, a novel discrete probability model that extends the classical Lindley distribution into the discrete domain. This distribution features two parameters, providing greater modeling flexibility and encompassing existing discrete models, such as the one-parameter discrete Lindley and geometric distributions. The paper thoroughly […]
Log-Inverse Gompertz Distribution: Properties and Application to Insurance and Soil Moisture Datasets
Unit-bounded distributions are often used to mimic values that are strictly defined inside the interval (0, 1). Despite this, these distributions are more uncommon than those with semi-bounded support (0, ∞). However, many real-life circumstances involve observations with a unit-bounded range, such as proportions, percentages, ratios, rates, and fractions. This study introduces the Log-Inverse Gompertz […]