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Aditya Chakraborty

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Articles

Modeling Healthcare Data with Logistic Quantile and Uniform Based Mixture Polynomial Distributions

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By Mohan Pant, Aditya Chakraborty, Jovanna Tracz
| preprints.org
You are already at the latest version Healthcare continuous data often deviate from normality, which can substantially increase the risk of making invalid inferences, given that many inferential statistical procedures rely on normality assumption. To obviate this issue, we propose a new family of non-normal distributions based on a linear combination of the quantile functions of standard logistic and uniform (0, 1) distributions.
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Modeling Non-normal Distributions with Mixed Third-Order Polynomials of Standard Normal and Logistic Variables

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By Mohan Pant, Aditya Chakraborty, Ismail El, Ismail El Moudden
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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An Analytical Prior Selection Procedure for Empirical Bayesian Analysis Using Resampling Techniques: A Simulation-Based Approach Using the Pancreatic Adenocarcinoma Data from the SEER Database

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By Aditya Chakraborty, Mohan Pant
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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