Comparison of Multivariate Adaptive Poisson Regression Spline and Multivariate Adaptive Generalized Poisson Regression Spline

Septia Devi Prihastuti Yasmirullah; Bambang Widjanarko Otok; Jerry Dwi Trijoyo Purnomo; Dedy Dwi Prastyo

doi:10.1063/5.0119385

Comparison of Multivariate Adaptive Poisson Regression Spline and Multivariate Adaptive Generalized Poisson Regression Spline

Septia Devi Prihastuti Yasmirullah^*
, Bambang Widjanarko Otok
, Jerry Dwi Trijoyo Purnomo
, Dedy Dwi Prastyo

^*Corresponding author for this work

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

Abstract

The multivariate adaptive regression (MARS) spline is a statistical method introduced by Friedman in 1991. The MARS method has several advantages, especially for data that consider the potential nonlinear pattern. These produce a continuous model on knots where the knot selection process is performed via adaptive procedures, capturing additive effects and interactions between predictor variables, and applied to data modeling with numerical and categorical responses. However, the analyzed data is not only numerical or categorical data, but also count type data. Count type data is often found in the health sector, for example, the number of data on tuberculosis. It invites to modify the MARS model with Poisson regression and generalized Poisson regression, i.e. Multivariate Adaptive Poisson Regression Spline (MAPRS) and Multivariate Adaptive Generalized Poisson Regression Spline (MAGPRS). In addition, this study aimed to compare MAPRS and MAGPRS when applied to tuberculosis data. By applying MAPRS and MAGPRS to model the number of tuberculosis in Lamongan regency, the MAPRS method outperforms the MAGPRS method. The MAPRS method has a lower RMSE value than the MAGPRS method.

Original language	English
Title of host publication	Proceedings of the International Conference on Advanced Technology and Multidiscipline, ICATAM 2021
Subtitle of host publication	"Advanced Technology and Multidisciplinary Prospective Towards Bright Future" Faculty of Advanced Technology and Multidiscipline
Editors	Prihartini Widiyanti, Prastika Krisma Jiwanti, Gunawan Setia Prihandana, Ratih Ardiati Ningrum, Rizki Putra Prastio, Herlambang Setiadi, Intan Nurul Rizki
Publisher	American Institute of Physics Inc.
ISBN (Electronic)	9780735444423
DOIs	https://doi.org/10.1063/5.0119385
Publication status	Published - 19 May 2023
Event	1st International Conference on Advanced Technology and Multidiscipline: Advanced Technology and Multidisciplinary Prospective Towards Bright Future, ICATAM 2021 - Virtual, Online Duration: 13 Oct 2021 → 14 Oct 2021

Publication series

Name	AIP Conference Proceedings
Volume	2536
ISSN (Print)	0094-243X
ISSN (Electronic)	1551-7616

Conference

Conference	1st International Conference on Advanced Technology and Multidiscipline: Advanced Technology and Multidisciplinary Prospective Towards Bright Future, ICATAM 2021
City	Virtual, Online
Period	13/10/21 → 14/10/21

UN SDGs

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

SDG 3 Good Health and Well-being

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10.1063/5.0119385

Cite this

Yasmirullah, S. D. P., Otok, B. W., Purnomo, J. D. T., & Prastyo, D. D. (2023). Comparison of Multivariate Adaptive Poisson Regression Spline and Multivariate Adaptive Generalized Poisson Regression Spline. In P. Widiyanti, P. K. Jiwanti, G. S. Prihandana, R. A. Ningrum, R. P. Prastio, H. Setiadi, & I. N. Rizki (Eds.), Proceedings of the International Conference on Advanced Technology and Multidiscipline, ICATAM 2021: "Advanced Technology and Multidisciplinary Prospective Towards Bright Future" Faculty of Advanced Technology and Multidiscipline Article 020005 (AIP Conference Proceedings; Vol. 2536). American Institute of Physics Inc.. https://doi.org/10.1063/5.0119385

Yasmirullah, Septia Devi Prihastuti ; Otok, Bambang Widjanarko ; Purnomo, Jerry Dwi Trijoyo et al. / Comparison of Multivariate Adaptive Poisson Regression Spline and Multivariate Adaptive Generalized Poisson Regression Spline. Proceedings of the International Conference on Advanced Technology and Multidiscipline, ICATAM 2021: "Advanced Technology and Multidisciplinary Prospective Towards Bright Future" Faculty of Advanced Technology and Multidiscipline. editor / Prihartini Widiyanti ; Prastika Krisma Jiwanti ; Gunawan Setia Prihandana ; Ratih Ardiati Ningrum ; Rizki Putra Prastio ; Herlambang Setiadi ; Intan Nurul Rizki. American Institute of Physics Inc., 2023. (AIP Conference Proceedings).

@inproceedings{64ff8b6a512e4816a8ee56d2fbe86b84,

title = "Comparison of Multivariate Adaptive Poisson Regression Spline and Multivariate Adaptive Generalized Poisson Regression Spline",

abstract = "The multivariate adaptive regression (MARS) spline is a statistical method introduced by Friedman in 1991. The MARS method has several advantages, especially for data that consider the potential nonlinear pattern. These produce a continuous model on knots where the knot selection process is performed via adaptive procedures, capturing additive effects and interactions between predictor variables, and applied to data modeling with numerical and categorical responses. However, the analyzed data is not only numerical or categorical data, but also count type data. Count type data is often found in the health sector, for example, the number of data on tuberculosis. It invites to modify the MARS model with Poisson regression and generalized Poisson regression, i.e. Multivariate Adaptive Poisson Regression Spline (MAPRS) and Multivariate Adaptive Generalized Poisson Regression Spline (MAGPRS). In addition, this study aimed to compare MAPRS and MAGPRS when applied to tuberculosis data. By applying MAPRS and MAGPRS to model the number of tuberculosis in Lamongan regency, the MAPRS method outperforms the MAGPRS method. The MAPRS method has a lower RMSE value than the MAGPRS method.",

author = "Yasmirullah, \{Septia Devi Prihastuti\} and Otok, \{Bambang Widjanarko\} and Purnomo, \{Jerry Dwi Trijoyo\} and Prastyo, \{Dedy Dwi\}",

note = "Publisher Copyright: {\textcopyright} 2023 American Institute of Physics Inc.. All rights reserved.; 1st International Conference on Advanced Technology and Multidiscipline: Advanced Technology and Multidisciplinary Prospective Towards Bright Future, ICATAM 2021 ; Conference date: 13-10-2021 Through 14-10-2021",

year = "2023",

month = may,

day = "19",

doi = "10.1063/5.0119385",

language = "English",

series = "AIP Conference Proceedings",

publisher = "American Institute of Physics Inc.",

editor = "Prihartini Widiyanti and Jiwanti, \{Prastika Krisma\} and Prihandana, \{Gunawan Setia\} and Ningrum, \{Ratih Ardiati\} and Prastio, \{Rizki Putra\} and Herlambang Setiadi and Rizki, \{Intan Nurul\}",

booktitle = "Proceedings of the International Conference on Advanced Technology and Multidiscipline, ICATAM 2021",

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Yasmirullah, SDP, Otok, BW , Purnomo, JDT & Prastyo, DD 2023, Comparison of Multivariate Adaptive Poisson Regression Spline and Multivariate Adaptive Generalized Poisson Regression Spline. in P Widiyanti, PK Jiwanti, GS Prihandana, RA Ningrum, RP Prastio, H Setiadi & IN Rizki (eds), Proceedings of the International Conference on Advanced Technology and Multidiscipline, ICATAM 2021: "Advanced Technology and Multidisciplinary Prospective Towards Bright Future" Faculty of Advanced Technology and Multidiscipline., 020005, AIP Conference Proceedings, vol. 2536, American Institute of Physics Inc., 1st International Conference on Advanced Technology and Multidiscipline: Advanced Technology and Multidisciplinary Prospective Towards Bright Future, ICATAM 2021, Virtual, Online, 13/10/21. https://doi.org/10.1063/5.0119385

Comparison of Multivariate Adaptive Poisson Regression Spline and Multivariate Adaptive Generalized Poisson Regression Spline. / Yasmirullah, Septia Devi Prihastuti; Otok, Bambang Widjanarko ; Purnomo, Jerry Dwi Trijoyo et al.
Proceedings of the International Conference on Advanced Technology and Multidiscipline, ICATAM 2021: "Advanced Technology and Multidisciplinary Prospective Towards Bright Future" Faculty of Advanced Technology and Multidiscipline. ed. / Prihartini Widiyanti; Prastika Krisma Jiwanti; Gunawan Setia Prihandana; Ratih Ardiati Ningrum; Rizki Putra Prastio; Herlambang Setiadi; Intan Nurul Rizki. American Institute of Physics Inc., 2023. 020005 (AIP Conference Proceedings; Vol. 2536).

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

TY - GEN

T1 - Comparison of Multivariate Adaptive Poisson Regression Spline and Multivariate Adaptive Generalized Poisson Regression Spline

AU - Yasmirullah, Septia Devi Prihastuti

AU - Otok, Bambang Widjanarko

AU - Purnomo, Jerry Dwi Trijoyo

AU - Prastyo, Dedy Dwi

PY - 2023/5/19

Y1 - 2023/5/19

N2 - The multivariate adaptive regression (MARS) spline is a statistical method introduced by Friedman in 1991. The MARS method has several advantages, especially for data that consider the potential nonlinear pattern. These produce a continuous model on knots where the knot selection process is performed via adaptive procedures, capturing additive effects and interactions between predictor variables, and applied to data modeling with numerical and categorical responses. However, the analyzed data is not only numerical or categorical data, but also count type data. Count type data is often found in the health sector, for example, the number of data on tuberculosis. It invites to modify the MARS model with Poisson regression and generalized Poisson regression, i.e. Multivariate Adaptive Poisson Regression Spline (MAPRS) and Multivariate Adaptive Generalized Poisson Regression Spline (MAGPRS). In addition, this study aimed to compare MAPRS and MAGPRS when applied to tuberculosis data. By applying MAPRS and MAGPRS to model the number of tuberculosis in Lamongan regency, the MAPRS method outperforms the MAGPRS method. The MAPRS method has a lower RMSE value than the MAGPRS method.

AB - The multivariate adaptive regression (MARS) spline is a statistical method introduced by Friedman in 1991. The MARS method has several advantages, especially for data that consider the potential nonlinear pattern. These produce a continuous model on knots where the knot selection process is performed via adaptive procedures, capturing additive effects and interactions between predictor variables, and applied to data modeling with numerical and categorical responses. However, the analyzed data is not only numerical or categorical data, but also count type data. Count type data is often found in the health sector, for example, the number of data on tuberculosis. It invites to modify the MARS model with Poisson regression and generalized Poisson regression, i.e. Multivariate Adaptive Poisson Regression Spline (MAPRS) and Multivariate Adaptive Generalized Poisson Regression Spline (MAGPRS). In addition, this study aimed to compare MAPRS and MAGPRS when applied to tuberculosis data. By applying MAPRS and MAGPRS to model the number of tuberculosis in Lamongan regency, the MAPRS method outperforms the MAGPRS method. The MAPRS method has a lower RMSE value than the MAGPRS method.

UR - https://www.scopus.com/pages/publications/85161417436

U2 - 10.1063/5.0119385

DO - 10.1063/5.0119385

M3 - Conference contribution

AN - SCOPUS:85161417436

T3 - AIP Conference Proceedings

BT - Proceedings of the International Conference on Advanced Technology and Multidiscipline, ICATAM 2021

A2 - Widiyanti, Prihartini

A2 - Jiwanti, Prastika Krisma

A2 - Prihandana, Gunawan Setia

A2 - Ningrum, Ratih Ardiati

A2 - Prastio, Rizki Putra

A2 - Setiadi, Herlambang

A2 - Rizki, Intan Nurul

PB - American Institute of Physics Inc.

T2 - 1st International Conference on Advanced Technology and Multidiscipline: Advanced Technology and Multidisciplinary Prospective Towards Bright Future, ICATAM 2021

Y2 - 13 October 2021 through 14 October 2021

ER -

Yasmirullah SDP, Otok BW , Purnomo JDT , Prastyo DD. Comparison of Multivariate Adaptive Poisson Regression Spline and Multivariate Adaptive Generalized Poisson Regression Spline. In Widiyanti P, Jiwanti PK, Prihandana GS, Ningrum RA, Prastio RP, Setiadi H, Rizki IN, editors, Proceedings of the International Conference on Advanced Technology and Multidiscipline, ICATAM 2021: "Advanced Technology and Multidisciplinary Prospective Towards Bright Future" Faculty of Advanced Technology and Multidiscipline. American Institute of Physics Inc. 2023. 020005. (AIP Conference Proceedings). doi: 10.1063/5.0119385

Comparison of Multivariate Adaptive Poisson Regression Spline and Multivariate Adaptive Generalized Poisson Regression Spline

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