The Estimation Function Approach Smoothing Spline Regression Analysis for Longitudinal Data

Risnawati; Adji Achmad Rinaldo Fernandes

doi:10.1088/1757-899X/546/5/052064

The Estimation Function Approach Smoothing Spline Regression Analysis for Longitudinal Data

Risnawati
, Adji Achmad Rinaldo Fernandes^*
, Nurjannah

^*Corresponding author for this work

Faculty of Mathematics and Natural Sciences

Research output: Contribution to journal › Conference article › peer-review

3 Citations (Scopus)

Abstract

It is given the paired data following a nonparametric regression model for longitudinal data. The regression curve is approached by the smoothing spline function. The smoothing spline is a function that is able to map the data well and has a small error variance. This current study aims to obtained from completing PWLS (Penalized Weighted Least Square) optimaziton. Besides, the GCV method is used to select the smoothing parameter.

Original language	English
Article number	052064
Journal	IOP Conference Series: Materials Science and Engineering
Volume	546
Issue number	5
DOIs	https://doi.org/10.1088/1757-899X/546/5/052064
Publication status	Published - 1 Jul 2019
Event	9th Annual Basic Science International Conference 2019, BaSIC 2019 - Malang, Indonesia Duration: 20 Mar 2019 → 21 Mar 2019

Access to Document

10.1088/1757-899X/546/5/052064

Cite this

@article{f48e1e2c04d54593a8b5caf5ec284b62,

title = "The Estimation Function Approach Smoothing Spline Regression Analysis for Longitudinal Data",

abstract = "It is given the paired data following a nonparametric regression model for longitudinal data. The regression curve is approached by the smoothing spline function. The smoothing spline is a function that is able to map the data well and has a small error variance. This current study aims to obtained from completing PWLS (Penalized Weighted Least Square) optimaziton. Besides, the GCV method is used to select the smoothing parameter.",

author = "Risnawati and \{Rinaldo Fernandes\}, \{Adji Achmad\} and Nurjannah",

note = "Publisher Copyright: {\textcopyright} Published under licence by IOP Publishing Ltd.; 9th Annual Basic Science International Conference 2019, BaSIC 2019 ; Conference date: 20-03-2019 Through 21-03-2019",

year = "2019",

month = jul,

day = "1",

doi = "10.1088/1757-899X/546/5/052064",

language = "English",

volume = "546",

journal = "IOP Conference Series: Materials Science and Engineering",

issn = "1757-8981",

publisher = "Institute of Physics",

number = "5",

}

TY - JOUR

T1 - The Estimation Function Approach Smoothing Spline Regression Analysis for Longitudinal Data

AU - Risnawati,

AU - Rinaldo Fernandes, Adji Achmad

AU - Nurjannah,

N1 - Publisher Copyright: © Published under licence by IOP Publishing Ltd.

PY - 2019/7/1

Y1 - 2019/7/1

N2 - It is given the paired data following a nonparametric regression model for longitudinal data. The regression curve is approached by the smoothing spline function. The smoothing spline is a function that is able to map the data well and has a small error variance. This current study aims to obtained from completing PWLS (Penalized Weighted Least Square) optimaziton. Besides, the GCV method is used to select the smoothing parameter.

AB - It is given the paired data following a nonparametric regression model for longitudinal data. The regression curve is approached by the smoothing spline function. The smoothing spline is a function that is able to map the data well and has a small error variance. This current study aims to obtained from completing PWLS (Penalized Weighted Least Square) optimaziton. Besides, the GCV method is used to select the smoothing parameter.

UR - https://www.scopus.com/pages/publications/85069470260

U2 - 10.1088/1757-899X/546/5/052064

DO - 10.1088/1757-899X/546/5/052064

M3 - Conference article

AN - SCOPUS:85069470260

SN - 1757-8981

VL - 546

JO - IOP Conference Series: Materials Science and Engineering

JF - IOP Conference Series: Materials Science and Engineering

IS - 5

M1 - 052064

T2 - 9th Annual Basic Science International Conference 2019, BaSIC 2019

Y2 - 20 March 2019 through 21 March 2019

ER -

The Estimation Function Approach Smoothing Spline Regression Analysis for Longitudinal Data

Abstract

Access to Document

Other files and links

Fingerprint

Cite this