Universiti Teknologi Malaysia Institutional Repository

Identifying outliers using generalized inner and outer fences

Adnan, Robiah and C. Schwertman, Neil and Setan, Halim and Mohamad, Mohd. Nor (2006) Identifying outliers using generalized inner and outer fences. In: Recent Advances in Probability and Statistics. Penerbit UTM, Johor , pp. 31-50. ISBN 978-983-52-0612-2

[img] PDF (Abstract)
10Kb

Official URL: http://www.penerbit.utm.my/bookchapterdoc/FS/bookc...

Abstract

Outliers are observations that appear inconsistent with the rest of the data set [1]. It is not unusual to find an average of 10% outlying observations in the data set of some processes. Frequently in regression analysis applications, the data set contains some observations that may have a profound impact or influence on the fitted least squares regression function. In general, influential observations are outliers and can have significant influence on the parametric test and therefore it is not surprising that the detection and accommodation of outliers have received considerable attention in the literature (for example, [2], [3], [4], [5])

Item Type:Book Section
Subjects:Q Science
Divisions:Science
ID Code:25724
Deposited By: Liza Porijo
Deposited On:25 May 2012 04:12
Last Modified:04 Jun 2014 05:17

Repository Staff Only: item control page