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Asymptotic Results For Empirical Processes In Informative Model Of Random Censorship From Both Sides, Abdurakhim Abdushukurov, Dilshod Mansurov Sep 2023

Asymptotic Results For Empirical Processes In Informative Model Of Random Censorship From Both Sides, Abdurakhim Abdushukurov, Dilshod Mansurov

Bulletin of National University of Uzbekistan: Mathematics and Natural Sciences

In the paper, the empirical process in informative model of random censorship from both sides is investigated. For it, the limit Gaussian process with mean zero is founded. Under investigating of empirical process, the characterization properties of the considered informative model is used. The properties of the semiparametric estimator by using methods of numerical modeling are discussed.


A New Generalized Gamma-Weibull Distribution And Its Applications, Nihimat Iyebuhola Aleshinloye, Samuel Adewale Aderoju, Alfred Adewole Abiodun, Bako Lukmon Taiwo Apr 2023

A New Generalized Gamma-Weibull Distribution And Its Applications, Nihimat Iyebuhola Aleshinloye, Samuel Adewale Aderoju, Alfred Adewole Abiodun, Bako Lukmon Taiwo

Al-Bahir Journal for Engineering and Pure Sciences

In this paper, a New Generalized Gamma-Weibull (NGGW) distribution is developed by compounding Weibull and generalized gamma distribution. Some mathematical properties such as moments, Rényi entropy and order statistics are derived and discussed. The maximum likelihood estimation (MLE) method is used to estimate the model parameters. The proposed model is applied to two real-life datasets to illustrate its performance and flexibility as compared to some other competing distributions. The results obtained show that the new distribution fits each of the data better than the other competing distributions.


Sars-Cov-2 Pandemic Analytical Overview With Machine Learning Predictability, Anthony Tanaydin, Jingchen Liang, Daniel W. Engels Jan 2021

Sars-Cov-2 Pandemic Analytical Overview With Machine Learning Predictability, Anthony Tanaydin, Jingchen Liang, Daniel W. Engels

SMU Data Science Review

Understanding diagnostic tests and examining important features of novel coronavirus (COVID-19) infection are essential steps for controlling the current pandemic of 2020. In this paper, we study the relationship between clinical diagnosis and analytical features of patient blood panels from the US, Mexico, and Brazil. Our analysis confirms that among adults, the risk of severe illness from COVID-19 increases with pre-existing conditions such as diabetes and immunosuppression. Although more than eight months into pandemic, more data have become available to indicate that more young adults were getting infected. In addition, we expand on the definition of COVID-19 test and discuss …


An Analysis Of The Career Length Of Professional Basketball Players, Kwame D. Fynn, Morgan Sonnenschein Aug 2012

An Analysis Of The Career Length Of Professional Basketball Players, Kwame D. Fynn, Morgan Sonnenschein

The Macalester Review

An interesting problem in professional basketball is predicting how long a player remains in the NBA League. Previous research on this problem has focused on factors such as race, performance in games, and size. We propose to analyze career duration in the NBA based on awards won, position played and biological variables such as height. Using Accelerated Failure Time models, Cox Proportional Hazards models and Kaplan-Meier analyses, we determine that both height and number of awards won lengthen career duration; however, only certain player positions significantly affect career length of a player.


Reducing Carcase Rejection : A Comparison Of Carcase Rejection Rates In Sheep Delivered Either Direct From Farm To Abattoir Or Via The Saleyard System, C L. Mcdonald Jan 1981

Reducing Carcase Rejection : A Comparison Of Carcase Rejection Rates In Sheep Delivered Either Direct From Farm To Abattoir Or Via The Saleyard System, C L. Mcdonald

Journal of the Department of Agriculture, Western Australia, Series 4

No abstract provided.