• Publications
  • Influence
A simple more general boxplot method for identifying outliers
Abstract The boxplot method (Exploratory Data Analysis, Addison-Wesley, Reading, MA, 1977) is a graphically-based method of identifying outliers which is appealing not only in its simplicity but alsoExpand
  • 91
  • 5
  • PDF
A Comparative Study On Some Methods For Handling Multicollinearity Problems
In regression, the objective is to explain the variation in one or more response variables, by associating this variation with proportional variation in one or more explanatory variables. A frequentExpand
  • 44
  • 3
  • PDF
The use of graphic rules in grade one to help identify children at risk of handwriting difficulties.
Previous researches on elementary grade handwriting revealed that pupils employ certain strategy when writing or drawing. The relationship between this strategy and the use of graphic rules has beenExpand
  • 19
  • 2
A Poisson model typically is assumed for count data. In many cases, there are many zeros in the dependent variable and because of these many zeros, the mean and the variance values of the dependentExpand
  • 7
  • 1
Adjustment of an Intensive Care Unit (ICU) Data in Fuzzy C-Regression Models
This research is an attempt to present a proper methodology in data modification by using analytical hierarchy process (AHP) technique and fuzzy c-mean (FCM) model. The continuous data were builtExpand
  • 2
  • 1
Investigating the impact of excess zeros on hurdle‐generalized Poisson regression model with right censored count data
Typically, a Poisson model is assumed for count data. In many cases, there are many zeros in the dependent variable, thus the mean is not equal to the variance value of the dependent variable.Expand
  • 12
  • 1
Identifying multiple outliers in linear regression :Robust fit and clustering approach
This research provides a clustering based approach for determining potential candidates for outliers.This is a modification of the method proposed by Serbert et.al (1998).It is based on using theExpand
  • 4
  • 1
  • PDF
Using Ridge Least Median Squares to Estimate the Parameter by Solving Multicollinearity and Outliers Problems
In the multiple linear regression analysis, the ridge regression estimator is often used to address the problem of multicollinearity. Besides multicollinearity, outliers also constitute a problem inExpand
  • 1
  • 1
  • PDF
Extraction of dynamic features from hand drawn data for the identification of children with handwriting difficulty.
Studies have shown that differences between children with and without handwriting difficulties lie not only in the written product (static data) but also in dynamic data of handwriting process. SinceExpand
  • 32
Multiple Outliers Detection Procedures in Linear Regression
Kertas kerja ini menghuraikan satu prosedur untuk mengenalpasti gandaan data terpenncil dalam regresi linear. Prosedur ini menggunakan kaedah penyesuan teguh iaitu kaedah kuasa dua trim terkecil danExpand
  • 18
  • PDF