Enhancing Reliability and Accuracy in Stochastic Growth Modeling: Method of Three Selected Points Approach
Growth models play a pivotal role in diverse fields, such as population dynamics, epidemiology, finance, and ecological systems. Traditionally, deterministic growth models have been extensively employed to capture various aspects of growth phenomena. However, in real-world scenarios, stochasticity is inherent in the data, challenging the suitability of deterministic models. Consequently, there is a growing interest […]
Discrete Exponentiated Generalized Family of Distributions
In this paper, exponentiated-G family of distributions is constructed as a new family of discrete distribution, using the general approach of discretization of a continuous distribution. Some statistical properties including quantiles, mean residual life, mean time to failure, mean time between failure, availability, Re ́nyi entropy, moments and order statistics are obtained. Discrete exponentiated inverted […]
On the Exchangeability Property in Causal Models
Exchangeability is one of the most important concepts in Bayesian probability theory [7], as well as in causal analysis, particularly within the theory based on the potential outcomes (see [18, 21, 23, 15]). In this paper, we propose a way to make explicit the link between the two concepts. We show they are almost coincident […]
Three-Dimensional Copulas: A Generalized Convex Mixture Copulas Strategy
Copulas are multi-dimensional probabilistic functions that play a crucial role in modeling complex dependence structures between random variables. The theory and applications of the three-dimensional case have attracted considerable interest in recent years. This article discusses recent developments in this specific topic and innovates in some aspects. More precisely, the first part proposed to fill […]
Statistical Properties of a Generalization Erlang Truncated Exponential Distribution with Applications and Its Bivariate Extension
Using power exponentiated family, this paper introduces the New Power Exponentiated Erlang-Truncated Exponential distribution as a new generalization of the Erlang-Truncated Exponential distribution. The suggested distribution has constant and increasing shapes for hazard rate function. Numerous structural characteristics are derived, including quantile function, moments, moment generating function, behavior of hazard, reversed hazard and cumulative hazard […]
Multi-Class Classification of Genetic Mutation Using Machine Learning Models
The challenge of distinguishing genetic mutations that contribute to tumor growth is crucial in cancer treatment. Cancer is responsible for millions of deaths annually, hence the need for early detection of tumors to improve treatment efficacy and survival rates. However, manual classification is prone to errors and inefficiencies due to human limitations and the complexity […]
A New Mixture of Two Components of Exponentiated Family with Applications to Real Life Data Sets
In this paper, the mixture of two components of exponentiated family is introduced as a new family of continuous distributions. Some general properties of the proposed family are discussed such as the quantile function, moments, moment generating function and order statistics. The maximum likelihood estimation method is used to derive the estimators for the unknown […]
Predicting Sleep Disorders: Leveraging Sleep Health and Lifestyle Data with Dipper Throated Optimization Algorithm for Feature Selection and Logistic Regression for Classification
This paper is a thorough examination of the modeling of sleep disorders based on machine learning that is applied to the sleep-health-and-lifestyle data. The use of the Dipper Throated Optimization Algorithm for feature selection and Logistic Regression for classification is the basis of the study that explores the effectiveness of predictive models in identifying sleep […]
A New Extention of the Odd Inverse Weibull-G Family of Distributions: Bayesian and Non-Bayesian Estimation with Engineering Applications
In this work, we propose a novel generator called the “extended odd inverse Weibull-generator” to obtain better distribution flexibility. This generator is considered as a generalization of the three well-known families. In comparison to the baseline model, the newly formed family may offer more efficient continuous symmetric and asymmetric models. The statistical features of the […]
On Fitting Renewable Energy Sources Data: Using a New Trigonometric Statistical Model
The goal of this work is to create an innovative heavy-tailed distribution known as the arctan-Kumaraswamy exponential (ATKE) distribution. The Kumaraswamy exponential distribution and the arctan-X family of distributions were combined to create the ATKE distribution. The ATKE distribution is adaptable and capable of modeling a range of hazard rate shapes when compared to the […]