Extended Lomax Distribution with an Application to Cancer Patient Data

Sher Chhetri; Denzyl Josh Lastimoso; Cory Ball

doi:10.1007/978-3-030-98012-2_22

Extended Lomax Distribution with an Application to Cancer Patient Data

Sher Chhetri, Denzyl Josh Lastimoso, Cory Ball

Risk Methods and Analysis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this work, we introduce a new four-parameter cubic rank transmuted Lomax (CRTL) distribution using the cubic rank transmutation map approach. The expressions for some mathematical properties of the proposed model are derived. The method of maximum likelihood is used to estimate the parameters of the distribution. To assess the performance of the model, goodness of fit measures, Akaike information criterion (AIC), the Bayesian information criterion (BIC), and the Hannan-Quinn information criterion (HQIC) are compared. The importance and flexibility of the new distribution is demonstrated by means of an application to bladder cancer patient data.

Original language	English
Title of host publication	Advances in Information and Communication - Proceedings of the 2022 Future of Information and Communication Conference, FICC
Editors	Kohei Arai
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	280-290
Number of pages	11
ISBN (Print)	9783030980115
DOIs	https://doi.org/10.1007/978-3-030-98012-2_22
State	Published - 2022
Event	Future of Information and Communication Conference, FICC 2022 - Virtual, Online Duration: Mar 3 2022 → Mar 4 2022

Publication series

Name	Lecture Notes in Networks and Systems
Volume	438 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	Future of Information and Communication Conference, FICC 2022
City	Virtual, Online
Period	03/3/22 → 03/4/22

Funding

Funding. Sher Chhetri was partially supported by University of South Carolina Sumter Summer Research Fund-2020.

Funders	Funder number
University of South Carolina Sumter Summer Research Fund-2020

Keywords

Cubic rank transmutation map
Lomax distribution
Maximum likelihood
Parameter estimation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-98012-2_22

Cite this

Chhetri, S., Lastimoso, D. J., & Ball, C. (2022). Extended Lomax Distribution with an Application to Cancer Patient Data. In K. Arai (Ed.), Advances in Information and Communication - Proceedings of the 2022 Future of Information and Communication Conference, FICC (pp. 280-290). (Lecture Notes in Networks and Systems; Vol. 438 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-98012-2_22

Chhetri, Sher ; Lastimoso, Denzyl Josh ; Ball, Cory. / Extended Lomax Distribution with an Application to Cancer Patient Data. Advances in Information and Communication - Proceedings of the 2022 Future of Information and Communication Conference, FICC. editor / Kohei Arai. Springer Science and Business Media Deutschland GmbH, 2022. pp. 280-290 (Lecture Notes in Networks and Systems).

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title = "Extended Lomax Distribution with an Application to Cancer Patient Data",

abstract = "In this work, we introduce a new four-parameter cubic rank transmuted Lomax (CRTL) distribution using the cubic rank transmutation map approach. The expressions for some mathematical properties of the proposed model are derived. The method of maximum likelihood is used to estimate the parameters of the distribution. To assess the performance of the model, goodness of fit measures, Akaike information criterion (AIC), the Bayesian information criterion (BIC), and the Hannan-Quinn information criterion (HQIC) are compared. The importance and flexibility of the new distribution is demonstrated by means of an application to bladder cancer patient data.",

keywords = "Cubic rank transmutation map, Lomax distribution, Maximum likelihood, Parameter estimation",

author = "Sher Chhetri and Lastimoso, {Denzyl Josh} and Cory Ball",

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language = "English",

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series = "Lecture Notes in Networks and Systems",

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Chhetri, S, Lastimoso, DJ & Ball, C 2022, Extended Lomax Distribution with an Application to Cancer Patient Data. in K Arai (ed.), Advances in Information and Communication - Proceedings of the 2022 Future of Information and Communication Conference, FICC. Lecture Notes in Networks and Systems, vol. 438 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 280-290, Future of Information and Communication Conference, FICC 2022, Virtual, Online, 03/3/22. https://doi.org/10.1007/978-3-030-98012-2_22

Extended Lomax Distribution with an Application to Cancer Patient Data. / Chhetri, Sher; Lastimoso, Denzyl Josh; Ball, Cory.
Advances in Information and Communication - Proceedings of the 2022 Future of Information and Communication Conference, FICC. ed. / Kohei Arai. Springer Science and Business Media Deutschland GmbH, 2022. p. 280-290 (Lecture Notes in Networks and Systems; Vol. 438 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Lastimoso, Denzyl Josh

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N2 - In this work, we introduce a new four-parameter cubic rank transmuted Lomax (CRTL) distribution using the cubic rank transmutation map approach. The expressions for some mathematical properties of the proposed model are derived. The method of maximum likelihood is used to estimate the parameters of the distribution. To assess the performance of the model, goodness of fit measures, Akaike information criterion (AIC), the Bayesian information criterion (BIC), and the Hannan-Quinn information criterion (HQIC) are compared. The importance and flexibility of the new distribution is demonstrated by means of an application to bladder cancer patient data.

AB - In this work, we introduce a new four-parameter cubic rank transmuted Lomax (CRTL) distribution using the cubic rank transmutation map approach. The expressions for some mathematical properties of the proposed model are derived. The method of maximum likelihood is used to estimate the parameters of the distribution. To assess the performance of the model, goodness of fit measures, Akaike information criterion (AIC), the Bayesian information criterion (BIC), and the Hannan-Quinn information criterion (HQIC) are compared. The importance and flexibility of the new distribution is demonstrated by means of an application to bladder cancer patient data.

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KW - Parameter estimation

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SN - 9783030980115

T3 - Lecture Notes in Networks and Systems

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BT - Advances in Information and Communication - Proceedings of the 2022 Future of Information and Communication Conference, FICC

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Chhetri S, Lastimoso DJ, Ball C. Extended Lomax Distribution with an Application to Cancer Patient Data. In Arai K, editor, Advances in Information and Communication - Proceedings of the 2022 Future of Information and Communication Conference, FICC. Springer Science and Business Media Deutschland GmbH. 2022. p. 280-290. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-030-98012-2_22

Extended Lomax Distribution with an Application to Cancer Patient Data

Abstract

Publication series

Conference

Funding

Keywords

UN SDGs

Access to Document

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