Modified multivariate adaptive regression spline and generalized Poisson regression

Riry Sriningsih; Bambang Widjanarko Otok

doi:10.1063/5.0204453

Modified multivariate adaptive regression spline and generalized Poisson regression

Riry Sriningsih
, Bambang Widjanarko Otok^*
, Sutikno

^*Corresponding author for this work

Institut Teknologi Sepuluh Nopember
State University of Padang

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

Abstract

This paper discusses model formation which is a modification between multivariate adaptive regression spline (MARS) and generalized Poisson regression (GPR). The maximum likelihood estimation method (MLE) is performed to determine the estimation of model parameters. Furthermore, the model was applied to cases of dengue hemorrhagic fever (DHF) in Java. The results obtained are estimates of model parameters that are not closed form. Therefore, it was solved by the Bernd Hall Hausman (BHHH) numerical method. The results of the application get a very good model on the basis of function = 16, maximum interaction = 3, and minimum observation = 1.

Original language	English
Title of host publication	AIP Conference Proceedings
Editors	Yerizon, Paulo Canas Rodrigues, Goh Khang Wen, Devni Prima Sari, Fridgo Tasman, Ronal Rifandi, Nurul Afifah Rusyda
Publisher	American Institute of Physics
Edition	1
ISBN (Electronic)	9780735449091
DOIs	https://doi.org/10.1063/5.0204453
Publication status	Published - 10 Apr 2024
Event	6th International Conference on Mathematics and Mathematics Education, ICM2E 2022 - Padang, Indonesia Duration: 3 Sept 2022 → 4 Sept 2022

Publication series

Name	AIP Conference Proceedings
Number	1
Volume	3024
ISSN (Print)	0094-243X
ISSN (Electronic)	1551-7616

Conference

Conference	6th International Conference on Mathematics and Mathematics Education, ICM2E 2022
Country/Territory	Indonesia
City	Padang
Period	3/09/22 → 4/09/22

UN SDGs

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

SDG 3 Good Health and Well-being

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10.1063/5.0204453

Cite this

Sriningsih, R., Otok, B. W., & Sutikno (2024). Modified multivariate adaptive regression spline and generalized Poisson regression. In Yerizon, P. C. Rodrigues, G. K. Wen, D. P. Sari, F. Tasman, R. Rifandi, & N. A. Rusyda (Eds.), AIP Conference Proceedings (1 ed.). Article 030002 (AIP Conference Proceedings; Vol. 3024, No. 1). American Institute of Physics. https://doi.org/10.1063/5.0204453

Sriningsih, Riry ; Otok, Bambang Widjanarko ; Sutikno. / Modified multivariate adaptive regression spline and generalized Poisson regression. AIP Conference Proceedings. editor / Yerizon ; Paulo Canas Rodrigues ; Goh Khang Wen ; Devni Prima Sari ; Fridgo Tasman ; Ronal Rifandi ; Nurul Afifah Rusyda. 1. ed. American Institute of Physics, 2024. (AIP Conference Proceedings; 1).

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title = "Modified multivariate adaptive regression spline and generalized Poisson regression",

abstract = "This paper discusses model formation which is a modification between multivariate adaptive regression spline (MARS) and generalized Poisson regression (GPR). The maximum likelihood estimation method (MLE) is performed to determine the estimation of model parameters. Furthermore, the model was applied to cases of dengue hemorrhagic fever (DHF) in Java. The results obtained are estimates of model parameters that are not closed form. Therefore, it was solved by the Bernd Hall Hausman (BHHH) numerical method. The results of the application get a very good model on the basis of function = 16, maximum interaction = 3, and minimum observation = 1.",

author = "Riry Sriningsih and Otok, \{Bambang Widjanarko\} and Sutikno",

note = "Publisher Copyright: {\textcopyright} 2024 Author(s).; 6th International Conference on Mathematics and Mathematics Education, ICM2E 2022 ; Conference date: 03-09-2022 Through 04-09-2022",

year = "2024",

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language = "English",

series = "AIP Conference Proceedings",

publisher = "American Institute of Physics",

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Sriningsih, R, Otok, BW & Sutikno 2024, Modified multivariate adaptive regression spline and generalized Poisson regression. in Yerizon, PC Rodrigues, GK Wen, DP Sari, F Tasman, R Rifandi & NA Rusyda (eds), AIP Conference Proceedings. 1 edn, 030002, AIP Conference Proceedings, no. 1, vol. 3024, American Institute of Physics, 6th International Conference on Mathematics and Mathematics Education, ICM2E 2022, Padang, Indonesia, 3/09/22. https://doi.org/10.1063/5.0204453

Modified multivariate adaptive regression spline and generalized Poisson regression. / Sriningsih, Riry; Otok, Bambang Widjanarko ; Sutikno.
AIP Conference Proceedings. ed. / Yerizon; Paulo Canas Rodrigues; Goh Khang Wen; Devni Prima Sari; Fridgo Tasman; Ronal Rifandi; Nurul Afifah Rusyda. 1. ed. American Institute of Physics, 2024. 030002 (AIP Conference Proceedings; Vol. 3024, No. 1).

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

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AU - Otok, Bambang Widjanarko

AU - Sutikno,

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N2 - This paper discusses model formation which is a modification between multivariate adaptive regression spline (MARS) and generalized Poisson regression (GPR). The maximum likelihood estimation method (MLE) is performed to determine the estimation of model parameters. Furthermore, the model was applied to cases of dengue hemorrhagic fever (DHF) in Java. The results obtained are estimates of model parameters that are not closed form. Therefore, it was solved by the Bernd Hall Hausman (BHHH) numerical method. The results of the application get a very good model on the basis of function = 16, maximum interaction = 3, and minimum observation = 1.

AB - This paper discusses model formation which is a modification between multivariate adaptive regression spline (MARS) and generalized Poisson regression (GPR). The maximum likelihood estimation method (MLE) is performed to determine the estimation of model parameters. Furthermore, the model was applied to cases of dengue hemorrhagic fever (DHF) in Java. The results obtained are estimates of model parameters that are not closed form. Therefore, it was solved by the Bernd Hall Hausman (BHHH) numerical method. The results of the application get a very good model on the basis of function = 16, maximum interaction = 3, and minimum observation = 1.

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M3 - Conference contribution

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T3 - AIP Conference Proceedings

BT - AIP Conference Proceedings

A2 - Yerizon, null

A2 - Rodrigues, Paulo Canas

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A2 - Sari, Devni Prima

A2 - Tasman, Fridgo

A2 - Rifandi, Ronal

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PB - American Institute of Physics

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Y2 - 3 September 2022 through 4 September 2022

ER -

Modified multivariate adaptive regression spline and generalized Poisson regression

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