TY - GEN
T1 - Interval Estimation for Nonparametric Regression Using Fourier Series Estimator in Longitudinal Data
AU - Fadillah Mardianto, M. Fariz
AU - Gunardi,
AU - Utami, Herni
N1 - Publisher Copyright:
© 2022 American Institute of Physics Inc.. All rights reserved.
PY - 2022/1/25
Y1 - 2022/1/25
N2 - Fourier series is developed in nonparametric regression for longitudinal data because of the demand data analysis with more complex in data structure. Nonparametric regression based on Fourier series estimator is capable to model data relationship with fluctuation or oscillation pattern, that represents with sine and cosine functions. For point estimation analysis, Penalized Weighted Least Square (PWLS) is used to determine an estimator for parameter vector in nonparametric regression. Different with previous studies, PWLS is used to get smooth estimator. Based on point estimation result with PWLS optimization, we develop further inference Statistics. The inference Statistics are interval estimation.Interval estimation can investigate the tolerance level from point estimation based on lower and upper bound and become fundamental discussion that related to hypothesis test. The main result is the lowest band confidence with lower and upper bound that related distribution from pivotal quantity. The interval confidence result is related to estimate based on regression curve with Fourier series estimator for longitudinal data.
AB - Fourier series is developed in nonparametric regression for longitudinal data because of the demand data analysis with more complex in data structure. Nonparametric regression based on Fourier series estimator is capable to model data relationship with fluctuation or oscillation pattern, that represents with sine and cosine functions. For point estimation analysis, Penalized Weighted Least Square (PWLS) is used to determine an estimator for parameter vector in nonparametric regression. Different with previous studies, PWLS is used to get smooth estimator. Based on point estimation result with PWLS optimization, we develop further inference Statistics. The inference Statistics are interval estimation.Interval estimation can investigate the tolerance level from point estimation based on lower and upper bound and become fundamental discussion that related to hypothesis test. The main result is the lowest band confidence with lower and upper bound that related distribution from pivotal quantity. The interval confidence result is related to estimate based on regression curve with Fourier series estimator for longitudinal data.
UR - http://www.scopus.com/inward/record.url?scp=85147277458&partnerID=8YFLogxK
U2 - 10.1063/5.0103799
DO - 10.1063/5.0103799
M3 - Conference contribution
AN - SCOPUS:85147277458
T3 - AIP Conference Proceedings
BT - 8th International Conference and Workshop on Basic and Applied Science, ICOWOBAS 2021
A2 - Wibowo, Anjar Tri
A2 - Mardianto, M. Fariz Fadillah
A2 - Rulaningtyas, Riries
A2 - Sakti, Satya Candra Wibawa
A2 - Imron, Muhammad Fauzul
A2 - Ramadhan, Rico
PB - American Institute of Physics Inc.
T2 - 8th International Conference and Workshop on Basic and Applied Science, ICOWOBAS 2021
Y2 - 25 August 2021 through 26 August 2021
ER -