Journal of Pharmacology Pharmaceutics & Pharmacovigilance Category: Medical Type: Short Communication
The Quantile Transmuted-Chen G Family of Distributions with Illustration to Breast Cancer Patients Data
- Clement Boateng Ampadu1*
- 1 Department Of Biostatistics, 31 Carrolton Road, Boston, MA 02132-6303, United States
*Corresponding Author:
Clement Boateng AmpaduDepartment Of Biostatistics, 31 Carrolton Road, Boston, MA 02132-6303, United States
Tel:+1 6174697268,
Email:drampadu@hotmail.com
Received Date: May 02, 2020 Accepted Date: May 07, 2020 Published Date: May 18, 2020
Abstract
The idea of transmuted distributions appeared. On the other hand, some contributions to quantile distribution theory appeared. Based on developments, we introduce the class of quantile transmuted-Chen G distributions, and show a sub-model is good in fitting the breast cancer patient’s data recorded.
Keywords
Breast cancer; Chen-G; Quantile distribution theory; Transmuted distributions
CONTENTS
- The New Family Illustrated
- Concluding Remarks and Further Recommendations
The New Family Illustrated
We begin with the following
Definition 1.1. A random variable J is claimed to follow the quantile transmuted- Chen G family of distributions [1] if its CDF can be represented by the following integral
From the above we have the following
Proposition 1.2. The CDF of the quantile transmuted- Chen G family of distributions [2,3] is given by
For illustrative purposes, let us assume the baseline distribution is Weibull with the following CDF
Theorem 1.3. The CDF of the quantile transmuted Chen-Weibull family is given by
Remark 1.4. We write J* ∼ QTCW(a, b, λ , c, d), if J* is a quantile transmuted Chen-Weibull random variable
This distribution is a good fit to real-life data as shown below (Figure 1).
Figure 1: The CDF of QTCW (1.82675, 125.674, 0.554331, 0.629088, 3.55831) fitted to the empirical distribution of the breast cancer patient’s data recorded in [5].
Concluding Remarks and Further Recommendations
The quantile transmuted Chen-G class of distributions is presented, a sub-model is shown to be a good fit to real life data [5] from the health sciences. The author invites the reader to investigate further properties and applications of this [6] new class of statistical distributions. Potential investigations include
- Application to Other Data Sets in the Health Sciences: We suggest the bladder cancer patient’s data recorded in [7], which accordingly is taken from [8].
- Clinical Applications: We suggest the vitamin A data set of [9]. This data set was designed to evaluate the effect of vitamin A supplementation on recurrent diarrheal episodes in small children. In particular, the authors of [10] modelled the treatment effect in time until the first occurrence of diarrheal episodes, using an appropriate regression model with censored data.
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Citation: Ampadu CB (2020) The Quantile Transmuted-Chen G Family of Distributions with Illustration to Breast Cancer Patients Data. J Pharmacol Pharmaceut Pharmacovig 4: 013.
Copyright: © 2020 Clement Boateng Ampadu, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
