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ibrahim Mohamed
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Mathematics

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Detection Procedure for A Single Outlier in a Bilinear Model 1azami Zaharim, 2mohammad Said Zainol, 3ibrahim Azami Zaharim; Mohammad Said Zainol; Ibrahim Mohamed; Mohd Sahar Yahaya
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 6, No 1 (2006)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v6i1.934

Abstract

A single outlier detection procedure for data generated from BL(1,1,1,1) models is developed. It iscarried out in three stages. Firstly, the measure of impact of an IO, AO, TC and LC, denoted by IO  ,AO  , TC  and LC  , respectively are derived based on least squares method. Secondly, test statisticsand test criteria are defined for classifying an observation as an outlier of its respective type. Finally,a general single outlier detection procedure is presented to distinguish a particular type of outlier at atime point t.
A Detection Measure of Outliers Based on Forward Search Approach for Cox-Regression Model Nor Akmal Md Noh; Ibrahim Mohamed; Nur Aishah Mohd Taib
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 8, No 2 (2008)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v8i2.984

Abstract

This paper focuses on identifying possible outliers based on Cox regression model. Forward searchmethod has been applied in several studies involving regression-based models such as linearregression and generalized linear model. The method starts with a pre-selected subset of a data set.The method moves forward through the data by adding observations one by one and progressivechanges in values of statistics are noted. In this paper, we extend the application of forward search insurvival data analysis. Currently, graphical methods are used to detect any significant changes invalues of the statistics. We propose a measure which may aid us in determining observations that areoutlier.
Co-Authors Azami Zaharim mohammad Said Zainol Mohd Sahar Yahaya Nor Akmal Md Noh Nur Aishah Mohd Taib