Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 5 de 5
Filter
1.
PLoS One ; 18(1): e0278659, 2023.
Article in English | MEDLINE | ID: covidwho-2197052

ABSTRACT

During the course of this research, we came up with a brand new distribution that is superior; we then presented and analysed the mathematical properties of this distribution; finally, we assessed its fuzzy reliability function. Because the novel distribution provides a number of advantages, like the reality that its cumulative distribution function and probability density function both have a closed form, it is very useful in a wide range of disciplines that are related to data science. One of these fields is machine learning, which is a sub field of data science. We used both traditional methods and Bayesian methodologies in order to generate a large number of different estimates. A test setup might have been carried out to assess the effectiveness of both the classical and the Bayesian estimators. At last, three different sets of Covid-19 death analysis were done so that the effectiveness of the new model could be demonstrated.


Subject(s)
COVID-19 , Humans , Bayes Theorem , Reproducibility of Results , COVID-19/epidemiology , Likelihood Functions
2.
Alexandria Engineering Journal ; 2022.
Article in English | ScienceDirect | ID: covidwho-2104239

ABSTRACT

The two-parameter classical Weibull distribution is commonly implemented to cater for the product’s reliability, model the failure rates, analyze lifetime phenomena, etc. In this work, we study a novel version of the Weibull model for analyzing real-life events in the sports and medical sectors. The newly derived version of the Weibull model, namely, a new cosine-Weibull (NC-Weibull) distribution. The importance of this research is that it suggests a novel version of the Weibull model without adding any additional parameters. Different distributional properties of the NC-Weibull distribution are obtained. The maximum likelihood approach is implemented to estimate the parameters of the NC-Weibull distribution. Finally, three applications are analyzed to prove the superiority of the NC-Weibull distribution over some other existing probability models considered in this study. The first and second applications, respectively, show the mortality rates of COVID-19 patients in Italy and Canada. Whereas, the third data set represents the injury rates of the basketball players collected during the 2008–2009 and 2018–2019 national basketball association seasons. Based on four selection criteria, it is observed that the NC-Weibull distribution may be a more suitable model for considering the sports and healthcare data sets.

3.
Complexity ; 2022, 2022.
Article in English | ProQuest Central | ID: covidwho-2079089

ABSTRACT

The extended reduced Kies distribution (ExRKD), which is an asymmetric flexible extension of the reduced Kies distribution, is the subject of this research. Some of its most basic mathematical properties are deduced from its formal definitions. We computed the ExRKD parameters using eight well-known methods. A full simulation analysis was done that allows the study of these estimators’ asymptotic behavior. The efficiency and applicability of the ExRKD are investigated via the modeling of COVID-19 and milk data sets, which demonstrates that the ExRKD delivers a better match to the data sets when compared to competing models.

4.
J Infect Dev Ctries ; 15(11): 1625-1629, 2021 11 30.
Article in English | MEDLINE | ID: covidwho-1572705

ABSTRACT

INTRODUCTION: This paper aims to measure the performance of early detection methods, which are usually used for infectious diseases. METHODOLOGY: By using real data of confirmed Coronavirus cases from the Kingdom of Saudi Arabia and Italy, the moving epidemic method (MEM) and the moving average cumulative sums (Mov. Avg Cusum) methods are used in our simulation study. RESULTS: Our results suggested that the CUSUM method outperforms the MEM in detecting the start of the Coronavirus outbreak.


Subject(s)
COVID-19/diagnosis , Diagnostic Tests, Routine , Early Diagnosis , SARS-CoV-2 , Benchmarking , COVID-19/epidemiology , Databases, Factual , Disease Outbreaks/prevention & control , Humans , Italy/epidemiology , Saudi Arabia/epidemiology
5.
Results Phys ; 26: 104260, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1240601

ABSTRACT

In this research article, we establish a fractional-order mathematical model to explore the infections of the coronavirus disease (COVID-19) caused by the novel SARS-CoV-2 virus. We introduce a set of fractional differential equations taking uninfected epithelial cells, infected epithelial cells, SARS-CoV-2 virus, and CTL response cell accounting for the lytic and non-lytic effects of immune responses. We also include the effect of a commonly used antiviral drug in COVID-19 treatment in an optimal control-theoretic approach. The stability of the equilibria of the fractional ordered system using qualitative theory. Numerical simulations are presented using an iterative scheme in Matlab in support of the analytical results.

SELECTION OF CITATIONS
SEARCH DETAIL