Authors:

KOMANG CANDRA IVAN, I WAYAN SUMARJAYA, MADE SUSILAWATI

Abstract:

“Circular data are data which the value in form of vector is circular data. Statistic analysis that is used in analyzing circular data is circular statistics analysis. In regression analysis, if any of predictor or response variables or both are circular then the regression analysis used is called circular regression analysis. Observation data in circular statistic which use direction and time units usually don’t satisfy all of the parametric assumptions, thus making nonparametric regression as a good solution. Nonparametric regression function estimation is using epanechnikov kernel estimator for the linier variables and von Mises kernel estimator for the circular variable. This study showed that the result of circular analysis by using circular descriptive statistic is better than common statistic. Multiple circular-linier nonparametric regressions with Epanechnikov and von Mises kernel estimator didn’t create estimation model explicitly as parametric regression does, but create estimation from its observation knots instead.”

Keywords

Keyword Not Available

Downloads:

Download data is not yet available.

References

References Not Available

PDF:

https://jurnal.harianregional.com/mtk/full-21298

Published

2016-05-31

How To Cite

IVAN, KOMANG CANDRA; SUMARJAYA, I WAYAN; SUSILAWATI, MADE. ANALISIS MODEL REGRESI NONPARAMETRIK SIRKULAR-LINEAR BERGANDA.E-Jurnal Matematika, [S.l.], v. 5, n. 2, p. 52 - 58, may 2016. ISSN 2303-1751. Available at: https://jurnal.harianregional.com/mtk/id-21298. Date accessed: 08 Jul. 2024. doi:https://doi.org/10.24843/MTK.2016.v05.i02.p121.

Citation Format

ABNT, APA, BibTeX, CBE, EndNote - EndNote format (Macintosh & Windows), MLA, ProCite - RIS format (Macintosh & Windows), RefWorks, Reference Manager - RIS format (Windows only), Turabian

Issue

Vol 5 No 2 (2016)

Section

Articles

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License