The boxplot method (Exploratory Data Analysis, Addison-Wesley, Reading, MA, 1977) is a graphicall... more 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 also because it does not use the extreme potential outliers in computing a measure of dispersion. The inner and outer fences are deÿned in terms of the hinges (or fourths), and therefore are not distorted by a few extreme values. Such distortion could lead to failing to detect some outliers, a problem known as "masking".
In regression, the objective is to explain the variation in one or more response variables, by as... more 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 frequent obstacle is that several of the explanatory variables will vary in rather similar ways. As a result, their collective power of explanation is considerably less than the sum of their individual powers. This phenomenon called multicollinearity, is a common problem in regression analysis. Handling multicollinearity problem in regression analysis is important because least squares estimations assume that predictor variables are not correlated with each other. The performances of ridge regression (RR), principal component regression (PCR) and partial least squares regression (PLSR) in handling multicollinearity problem in simulated data sets are compared to help and give future researchers a comprehensive view about the best procedure to handle multicollinearity problems. PCR is a combination of principal component analysis (PCA) and ordinary least squares regression (OLS) while PLSR is an approach similar to PCR because a component that can be used to reduce the number of variables need to be constructed. RR on the other hand is the modified least square method that allows a biased but more precise estimator. The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases were less than the number of observations used. The goal was to develop a linear equation that relates all the predictor variables to a response variable. For comparison purposes, mean square errors (MSE) were calculated. A Monte Carlo simulation study was used to evaluate the effectiveness of these three procedures. The analysis including all simulations and calculations were done using statistical package S-Plus 2000 software.
This paper describes a procedure for identifying multiple outliers in linear regression. This pro... more This paper describes a procedure for identifying multiple outliers in linear regression. This procedure uses a robust fit which is the least of trimmed of squares (LTS) and the single linkage clustering method to obtain the potential outliers. Then multiple-case diagnostics are used to obtain the outliers from these potential outliers. The performance of this procedure is also compared to Serbert's method. Monte Carlo simulations are used in determining which procedure performed best in all of the linear regression scenarios.
... ИНФОРМАЦИЯ О ПУБЛИКАЦИИ. Название публикации, A MULTIVARIATE CONTROL CHART FOR EXPECTED CHANG... more ... ИНФОРМАЦИЯ О ПУБЛИКАЦИИ. Название публикации, A MULTIVARIATE CONTROL CHART FOR EXPECTED CHANGES OVER TIME. Авторы, Neil C Schwertman, Thomas P Ryan, RobiahAdnan. Журнал, Quality Engineering. Издательство, Proquest ABI/INFORM. ...
Incineration is known to be the best available option for treating clinical waste, particularly t... more Incineration is known to be the best available option for treating clinical waste, particularly the pathological related waste. A proper operation of the incinerator is essential to ensure complete destruction of the waste. It is anticipated that variables such as feed rate (waste), both the combustion temperatures of the Primary Combustion Chamber (PCC) and Secondary Combustion Chamber (SCC), fuel and combustion air consumption play a major role in affecting the performance of the incineration process. Particularly, the combustion efficiency (one of the performance indicators) of the incinerator determined by the presence of carbon monoxide and carbon dioxide emission after the SCC must be continuously monitored. In this regard, a study to investigate the relationship between variables affecting the combustion efficiency, namely waste, temperatures and fuel, were performed using regression analysis and further verified by ANOVA. Results showed that waste, primary and secondary combustion temperatures contribute significantly to the combustion efficiency of the process. The correlation between these affecting variables were also investigated and discussed in the paper.
This research provides a clustering based approach for determining potential candidates for outli... more 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 the single linkage clustering algorithm to group the standardized predicted and residual values of data set fit by least trimmed of squares (LTS).
The new fuzzy c-regression modeling (FcRM) are widely used in order to fit switching regression m... more The new fuzzy c-regression modeling (FcRM) are widely used in order to fit switching regression models. Minimization of objective function yields immediate estimates for different c regression models. The functions of model, estimation technique and results are discussed in this paper. A case study in miles per gallon (MPG) of different cars using the FcRM modeling was carried out. The 3D graph for significant independent variables for FcRM clustering is shown in this study. The comparison between multiple linear regression and FcRM modeling were done. The mean square error (MSE) was used to find the better model. It was found that the FcRM modeling with lower MSE to be the better model and has great capability in predicting the dependent variable effectively.
Intense convective rain cells are often responsible for extreme hydrometeorological events includ... more Intense convective rain cells are often responsible for extreme hydrometeorological events including the majority of flash flood episodes, which is one of the most common and destructive weather-related phenomena especially in urban areas of Malaysia. Both ground and ...
There have been considerable interest in recent years in the detection and accommodation of multi... more There have been considerable interest in recent years in the detection and accommodation of multiple outliers in linear regression. However, most of them are complicated and unappealing to users with no mathematical background. The clustering algorithm from Sebert et al. ...
Zainal Abidin, Wardah and Sudin, Izman and Abdul Rani, Mat Rebi and Adnan, Robiah and Ahmad, Fare... more Zainal Abidin, Wardah and Sudin, Izman and Abdul Rani, Mat Rebi and Adnan, Robiah and Ahmad, Farediah (2007) A re-examination of the generic skills implementation programme in UTM: proposal for a strategic revision. In: Simposium Pengajaran & Pembelajaran UTM ...
The boxplot method (Exploratory Data Analysis, Addison-Wesley, Reading, MA, 1977) is a graphicall... more 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 also because it does not use the extreme potential outliers in computing a measure of dispersion. The inner and outer fences are deÿned in terms of the hinges (or fourths), and therefore are not distorted by a few extreme values. Such distortion could lead to failing to detect some outliers, a problem known as "masking".
In regression, the objective is to explain the variation in one or more response variables, by as... more 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 frequent obstacle is that several of the explanatory variables will vary in rather similar ways. As a result, their collective power of explanation is considerably less than the sum of their individual powers. This phenomenon called multicollinearity, is a common problem in regression analysis. Handling multicollinearity problem in regression analysis is important because least squares estimations assume that predictor variables are not correlated with each other. The performances of ridge regression (RR), principal component regression (PCR) and partial least squares regression (PLSR) in handling multicollinearity problem in simulated data sets are compared to help and give future researchers a comprehensive view about the best procedure to handle multicollinearity problems. PCR is a combination of principal component analysis (PCA) and ordinary least squares regression (OLS) while PLSR is an approach similar to PCR because a component that can be used to reduce the number of variables need to be constructed. RR on the other hand is the modified least square method that allows a biased but more precise estimator. The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases were less than the number of observations used. The goal was to develop a linear equation that relates all the predictor variables to a response variable. For comparison purposes, mean square errors (MSE) were calculated. A Monte Carlo simulation study was used to evaluate the effectiveness of these three procedures. The analysis including all simulations and calculations were done using statistical package S-Plus 2000 software.
This paper describes a procedure for identifying multiple outliers in linear regression. This pro... more This paper describes a procedure for identifying multiple outliers in linear regression. This procedure uses a robust fit which is the least of trimmed of squares (LTS) and the single linkage clustering method to obtain the potential outliers. Then multiple-case diagnostics are used to obtain the outliers from these potential outliers. The performance of this procedure is also compared to Serbert's method. Monte Carlo simulations are used in determining which procedure performed best in all of the linear regression scenarios.
... ИНФОРМАЦИЯ О ПУБЛИКАЦИИ. Название публикации, A MULTIVARIATE CONTROL CHART FOR EXPECTED CHANG... more ... ИНФОРМАЦИЯ О ПУБЛИКАЦИИ. Название публикации, A MULTIVARIATE CONTROL CHART FOR EXPECTED CHANGES OVER TIME. Авторы, Neil C Schwertman, Thomas P Ryan, RobiahAdnan. Журнал, Quality Engineering. Издательство, Proquest ABI/INFORM. ...
Incineration is known to be the best available option for treating clinical waste, particularly t... more Incineration is known to be the best available option for treating clinical waste, particularly the pathological related waste. A proper operation of the incinerator is essential to ensure complete destruction of the waste. It is anticipated that variables such as feed rate (waste), both the combustion temperatures of the Primary Combustion Chamber (PCC) and Secondary Combustion Chamber (SCC), fuel and combustion air consumption play a major role in affecting the performance of the incineration process. Particularly, the combustion efficiency (one of the performance indicators) of the incinerator determined by the presence of carbon monoxide and carbon dioxide emission after the SCC must be continuously monitored. In this regard, a study to investigate the relationship between variables affecting the combustion efficiency, namely waste, temperatures and fuel, were performed using regression analysis and further verified by ANOVA. Results showed that waste, primary and secondary combustion temperatures contribute significantly to the combustion efficiency of the process. The correlation between these affecting variables were also investigated and discussed in the paper.
This research provides a clustering based approach for determining potential candidates for outli... more 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 the single linkage clustering algorithm to group the standardized predicted and residual values of data set fit by least trimmed of squares (LTS).
The new fuzzy c-regression modeling (FcRM) are widely used in order to fit switching regression m... more The new fuzzy c-regression modeling (FcRM) are widely used in order to fit switching regression models. Minimization of objective function yields immediate estimates for different c regression models. The functions of model, estimation technique and results are discussed in this paper. A case study in miles per gallon (MPG) of different cars using the FcRM modeling was carried out. The 3D graph for significant independent variables for FcRM clustering is shown in this study. The comparison between multiple linear regression and FcRM modeling were done. The mean square error (MSE) was used to find the better model. It was found that the FcRM modeling with lower MSE to be the better model and has great capability in predicting the dependent variable effectively.
Intense convective rain cells are often responsible for extreme hydrometeorological events includ... more Intense convective rain cells are often responsible for extreme hydrometeorological events including the majority of flash flood episodes, which is one of the most common and destructive weather-related phenomena especially in urban areas of Malaysia. Both ground and ...
There have been considerable interest in recent years in the detection and accommodation of multi... more There have been considerable interest in recent years in the detection and accommodation of multiple outliers in linear regression. However, most of them are complicated and unappealing to users with no mathematical background. The clustering algorithm from Sebert et al. ...
Zainal Abidin, Wardah and Sudin, Izman and Abdul Rani, Mat Rebi and Adnan, Robiah and Ahmad, Fare... more Zainal Abidin, Wardah and Sudin, Izman and Abdul Rani, Mat Rebi and Adnan, Robiah and Ahmad, Farediah (2007) A re-examination of the generic skills implementation programme in UTM: proposal for a strategic revision. In: Simposium Pengajaran & Pembelajaran UTM ...
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