<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>A new Lomax Rayleigh distribution (NLRD) is proposed and generated using Transformed Transformer (T-X) family generator. Various structural properties like generating functions, moments, limiting form, quantile function median and mode of NLRD are studied. Maximum likelihood estimators (MLEs) of the parameters are obtained and the model fitting is tested with simulated data. Model adequacy with live data is explained with two real-time cancer data sets. The NLRD shows a better fit in the estimation of survival in bile duct cancer and head and neck cancer data than other existing distributions.</p>
</abstract>

A new Lomax Rayleigh distribution (NLRD) is proposed and generated using Transformed Transformer (T-X) family generator. Various structural properties like generating functions, moments, limiting form, quantile function median and mode of NLRD are studied. Maximum likelihood estimators (MLEs) of the parameters are obtained and the model fitting is tested with simulated data. Model adequacy with live data is explained with two real-time cancer data sets. The NLRD shows a better fit in the estimation of survival in bile duct cancer and head and neck cancer data than other existing distributions.

Survival analysis of cancer patients using a new Lomax Rayleigh distribution

Journal of Applied Mathematics, Statistics and Informatics

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Survival analysis of cancer patients using a new Lomax Rayleigh distribution"}

A new Lomax Rayleigh distribution (NLRD) is proposed and generated using Transformed Transformer (T-X) family generator. Various structural properties like...

Survival analysis of cancer patients using a new Lomax Rayleigh distribution

Pubblicato online: 09 giu 2023

Pagine: 19 - 45

DOI: https://doi.org/10.2478/jamsi-2023-0002

Parole chiave
Lomax Rayleigh distribution, properties, application, survival analysis, maximum likelihood estimation, head and neck cancer data

© 2023 K. Naga Saritha et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Survival analysis of cancer patients using a new Lomax Rayleigh distribution

Pubblicato online: 09 giu 2023

Pagine: 19 - 45

DOI: https://doi.org/10.2478/jamsi-2023-0002

Parole chiaveLomax Rayleigh distribution, properties, application, survival analysis, maximum likelihood estimation, head and neck cancer data

© 2023 K. Naga Saritha et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Lomax Rayleigh distribution, properties, application, survival analysis, maximum likelihood estimation, head and neck cancer data