Publication:
Curve Fitting With Bootstrap Error Analysis And Its Application On Two-Dimensional Data

Simple item page
dc.contributor.authorSahubar Ali, Nur Soffiah
dc.date.accessioned2025-09-26T07:37:30Z
dc.date.available2025-09-26T07:37:30Z
dc.date.issued2019-08
dc.description.abstractIn data fitting, researchers use various methods to determine the quality of a fitting. Visualization of images is crucial in observing the behavior of data obtained. The problem in judging the accuracy of a result obtained through visual observation are commonly faced by researchers when handling contaminated data such as noisy data, missing data and outliers. In this research, study has been conducted to deal with those noisy data and missing data using least square titting (LSF).
dc.identifier.urihttps://erepo.usm.my/handle/123456789/22640
dc.language.isoen
dc.subjectCurve fitting
dc.subjectLeast squares
dc.titleCurve Fitting With Bootstrap Error Analysis And Its Application On Two-Dimensional Data
dc.typeResource Types::text::thesis::doctoral thesis
dspace.entity.typePublication
oairecerif.author.affiliationUniversiti Sains Malaysia
Files
Collections
Pusat Pengajian Sains Matematik - Tesis