Journal of Applied Sciences and Environmental Management
This paper proposed the Exponentiated Complementary Kumaraswamy - G Power (ECK-GP) Series family ... more This paper proposed the Exponentiated Complementary Kumaraswamy - G Power (ECK-GP) Series family of distributions which is an extension of the Complementary Kumaraswamy-G Power Series family of distributions. The expressions for its densities, basic statistical properties and parameters estimation using the method of Maximum Likelihood were derived and established. An application of the Exponentiated Complementary Kumaraswamy Exponential Poisson (ECKEP) distribution to a real lifetime dataset clearly reveals its suitability and flexibility in fitting real life dataset.
A novel distribution called the Juchez distribution is proposed and studied. This distribution is... more A novel distribution called the Juchez distribution is proposed and studied. This distribution is composite of both exponential and gamma distributions. The properties and features of this distribution are studied, with empirical emphasis: on the inequality relationship within the measures of central tendency, and the coefficient of variation. The model parameter was estimated using the method of maximum likelihood, where the asymptotic and consistent properties are numerically studied as well. The flexibility of this distribution is shown, through an application to a facebook Live-Streaming and Cancer data set. This distribution shows a high efficiency when compared with other one parameter distributions.
The modeling phase of response surface methodology (RSM) involves the application of regression t... more The modeling phase of response surface methodology (RSM) involves the application of regression techniques to fitting a curve to the data generated from a designed experiment. The model-robust regression 2 (MRR2) method is a semi-parametric regression approach that combines portions of estimates from both the parametric and the nonparametric regression approaches via a mixing parameter. However, the robustness of the estimates from the MRR2 approach depends largely on the choice of bandwidth. Utilizing the cross-validation approach to bandwidth selection, we propose a methodology for deriving a data-driven function that generates local bandwidths for the MRR2 approach. Using two examples from the literature and a simulation study, we show that, in comparison with other regression methods, the results obtained from the MRR2 approach utilizing the proposed function offer remarkable improvements in the goodnessof-fit statistics.
Over the past decade, there have been rapid advances in the development of methods for the design... more Over the past decade, there have been rapid advances in the development of methods for the design and analysis of optimal split-plot experiment. Industrial experimentation involving optimality criteria has not been fully exhausted. In this study, we present a literature review on the development of optimal design of split-plot experiments. Split-plot designs, optimality criteria are discussed. Recent developments of optimal split-plot designs is evaluated and compared. Keywords : Optimality, Designs, Experiment, Randomization, Split-plot, Algorithm, Blocks.
The modeling phase of response surface methodology (RSM) involves the application of regression t... more The modeling phase of response surface methodology (RSM) involves the application of regression techniques to fitting a curve to the data generated from a designed experiment. The model-robust regression 2 (MRR2) method is a semi-parametric regression approach that combines portions of estimates from both the parametric and the nonparametric regression approaches via a mixing parameter. However, the robustness of the estimates from the MRR2 approach depends largely on the choice of bandwidth. Utilizing the cross-validation approach to bandwidth selection, we propose a methodology for deriving a data-driven function that generates local bandwidths for the MRR2 approach. Using two examples from the literature and a simulation study, we show that, in comparison with other regression methods, the results obtained from the MRR2 approach utilizing the proposed function offer remarkable improvements in the goodnessof-fit statistics.
Objective: In modeling environment processes, multi-disciplinary methods are used to explain, exp... more Objective: In modeling environment processes, multi-disciplinary methods are used to explain, explore and predict how the earth responds to natural human-induced environmental changes over time. Consequently, when analyzing spatial processes spatial domains, the spatial covariance of interest are always heterogeneous. However, this article proposed locally adaptive covariance for the spatial domain whose covariance is nonstationary in their spatial domain. The objectives of the study are to propose parametric, non-parametric and semi-parametric models for nonstationary spatial structure, continuous model for nonstationary spatial processes whose distance is far apart and to propose the adaptive weighting scheme approach that generates the optimal value for the nonparametric and semi-parametric models. Material and Methods: The spatial covariances are derived by applying the concept of adaptive weighting scheme approach on the covariance proposed in Nott and Dunsmuir (2002). Conseque...
The study introduced an algorithm for generating optimal split-plot designs. The designs were con... more The study introduced an algorithm for generating optimal split-plot designs. The designs were considered as optimal because they were capable and ecient in estimating the xed e ects of the statistical model that is appropriate given the split-plot design structure. Here, we introduced I-optimal design of split-plot experiments. The algorithm used in this research does not require the prior speci cation of a candidate set. Therefore, making the design of split-plot experiments computationally feasible in situations where the candidate set is too large to be tractable. Flexible choice of the sample size, inclusion of both continuous and categorical factors were allowed by this method. We show through an example the substantial bene ts of this method.
This study aims at investigating the satisfaction level of Automated Teller Machine (ATM) users i... more This study aims at investigating the satisfaction level of Automated Teller Machine (ATM) users in a Nigerian University (University of Benin, Benin City, Nigeria: A case study). We observed that there were no differences in the mean knowledge of ATM features among the sex and status of the staff and students (respondents) of the University. The study also revealed that the staff and students of the University are satisfied with the present ATM facilities in the University, but preferred 200 naira notes to the present 500 and 1000 naira notes being dispensed by ATM at various locations in the University. Keywords : Automated Teller Machine, questionnaire, respondent, satisfaction, surcharge, hypothesis.
Over the past decade, there have been rapid advances in the development of methods for the design... more Over the past decade, there have been rapid advances in the development of methods for the design and analysis of optimal split-plot experiment. Industrial experimentation involving optimality criteria has not been fully exhausted. In this study, we present a literature review on the development of optimal design of split-plot experiments. Split-plot designs, optimality criteria are discussed. Recent developments of optimal split-plot designs is evaluated and compared. Keywords : Optimality, Designs, Experiment, Randomization, Split-plot, Algorithm, Blocks.
The study introduced an algorithm for generating optimal split-plot designs. The designs were con... more The study introduced an algorithm for generating optimal split-plot designs. The designs were considered as optimal because they were capable and ecient in estimating the xed e ects of the statistical model that is appropriate given the split-plot design structure. Here, we introduced I-optimal design of split-plot experiments. The algorithm used in this research does not require the prior speci cation of a candidate set. Therefore, making the design of split-plot experiments computationally feasible in situations where the candidate set is too large to be tractable. Flexible choice of the sample size, inclusion of both continuous and categorical factors were allowed by this method. We show through an example the substantial bene ts of this method.
This paper investigates the finite sample performance of power and size properties of several maj... more This paper investigates the finite sample performance of power and size properties of several major co-integration tests using simulation analysis. These tests include; the co-integration Regression Durbin-Watson test (CRDW), Eagle-Granger test, Dicky Fuller unit root test with () statistics, Johansen likelihood ratio tests, and Phillips-Ouliaris test. Comparisons of tests are evaluated based on the proportion of rejects of the hypothesis of a no co-integration. This study answers the question of which co-integration test is better, particularly between the Eagle-Granger two-step test and the Johansen’s tests for co-integration, when the sets of parameters in models are persistence and spiky. The bivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH(1,1)) model with Gaussian innovations, is used in the data generating process (DGP). Our simulation results reveal that there is size distortion in the different co-integration test considered. The Eagle-Granger two-...
International Journal of Scientific & Technology Research, 2013
In this paper we presented the multivariate extension of multiple linear regression using Jackkni... more In this paper we presented the multivariate extension of multiple linear regression using Jackknife techniques in modeling the relationship between m set of responses 1 2 , , , m Y Y Y and a single set of r regressors 1 2 , , , m Z Z Z . The responses are Oil Import 1 ( ), Y Non-Oil Import 2 ( ), Y Oil Export 3 ( ), Y Non-Oil Export 4 ( ) Y which is classified as Nigeria Foreign Trade, while the regressors are Exchange Rate of US Dollar 1 ( ), Z and Exchange Rate of Pounds sterling’s 2 ( ) Z which are classified as Foreign Exchange Rate. We proposed new algorithm for estimating the parameters of multivariate linear regression using the jackknife technique. The results obtained using Jackknife delete-5 algorithm competes favorably with the existing methods. Consequently Time Series approach was adopted for future prediction of the Nigeria Foreign Trade from year 2011 to 2020. Evidently, the time series plot depicts an increase of exchange rate of US Dollar and Pounds Sterling ove...
Communications in Statistics - Theory and Methods, 2017
This paper presents a new criterion for selecting a two-level fractional factorial design. The th... more This paper presents a new criterion for selecting a two-level fractional factorial design. The theoretical underpinning for the criterion is the Shannon entropy. The criterion, which is referred to as the entropy-based minimum aberration criterion, has several advantages. The advantage of the entropy-based criterion over the classical minimum aberration criterion is that it utilises a measure of uncertainty on the skewness of the distribution of word length patterns in the selection of the 'best' design in a family of two-level fractional factorial plans. The criterion evades the trauma associated with the lack of prior knowledge on the important effects.
In this paper, we propose Complementary Kumaraswamy Weibull Power Series (CKWPS) Distributions. T... more In this paper, we propose Complementary Kumaraswamy Weibull Power Series (CKWPS) Distributions. The method is obtained by compounding the Kumaraswamy-G distribution and Power Series distribution on a latent complementary distance problem base. The mathematical properties of the proposed class of distribution are studied. The method of Maximum Likelihood Estimation is used for obtaining the estimates of the model parameters. A member of the family is investigated in detail. Finally an application of the proposed class is illustrated using a real data set.
Journal of Modern Applied Statistical Methods, 2014
Model-Robust Regression 2 (MRR2) method is a semi-parametric regression approach that combines pa... more Model-Robust Regression 2 (MRR2) method is a semi-parametric regression approach that combines parametric and nonparametric fits. The bandwidth controls the smoothness of the nonparametric portion. We present a methodology for deriving data-driven local bandwidth that enhances the performance of MRR2 method for fitting curves to data generated from designed experiments.
This paper proposes an algorithm for the estimation of the parameters of logistic regression anal... more This paper proposes an algorithm for the estimation of the parameters of logistic regression analysis using Jackknife. Jackknife delete-one and deleted algorithm was used to provide estimates of logistic regression coefficient. The Jackknife standard deviation provides an estimate of variability of the standard deviation of sample and it is a good measure of precision. The method was illustrated with real life data; and the results obtained from the Jackknife samples was compared with the result from ordinary logistic regression using the maximum likelihood method and results obtained reveals that the values from the jackknife algorithm for the parameter estimation, standard deviation and confidence interval were so close to the result from ordinary logistic regression analysis, this provides a good approximation to the result which shows that there is no bias in the jackknife coefficients.
This paper proposes an algorithm for the estimation of the parameters of logistic regression anal... more This paper proposes an algorithm for the estimation of the parameters of logistic regression analysis using Jackknife. Jackknife delete-one and deleted algorithm was used to provide estimates of logistic regression coefficient. The Jackknife standard deviation provides an estimate of variability of the standard deviation of sample and it is a good measure of precision. The method was illustrated with real life data; and the results obtained from the Jackknife samples was compared with the result from ordinary logistic regression using the maximum likelihood method and results obtained reveals that the values from the jackknife algorithm for the parameter estimation, standard deviation and confidence interval were so close to the result from ordinary logistic regression analysis, this provides a good approximation to the result which shows that there is no bias in the jackknife coefficients.
American Journal of Mathematics and Statistics, 2012
We constructed an) (2 s E-optimal supersaturated design (SSD) with an experimental run-size, n = ... more We constructed an) (2 s E-optimal supersaturated design (SSD) with an experimental run-size, n = 20 and number of factors, m = 57 (mu ltip le of 19). The construction is based on balanced incomplete block designs using a theorem proposed by Bulutoglu and Cheng. This is achieved by constructing the initial b locks of the balanced inco mplete block design using the theorem. Consequently, all other blocks are generated to constitute a balanced incomplete block design (BIBD),and the complete blocks that constitute the BIBD is transformed into the required supersaturated design(SSD).
Journal of Applied Sciences and Environmental Management
This paper proposed the Exponentiated Complementary Kumaraswamy - G Power (ECK-GP) Series family ... more This paper proposed the Exponentiated Complementary Kumaraswamy - G Power (ECK-GP) Series family of distributions which is an extension of the Complementary Kumaraswamy-G Power Series family of distributions. The expressions for its densities, basic statistical properties and parameters estimation using the method of Maximum Likelihood were derived and established. An application of the Exponentiated Complementary Kumaraswamy Exponential Poisson (ECKEP) distribution to a real lifetime dataset clearly reveals its suitability and flexibility in fitting real life dataset.
A novel distribution called the Juchez distribution is proposed and studied. This distribution is... more A novel distribution called the Juchez distribution is proposed and studied. This distribution is composite of both exponential and gamma distributions. The properties and features of this distribution are studied, with empirical emphasis: on the inequality relationship within the measures of central tendency, and the coefficient of variation. The model parameter was estimated using the method of maximum likelihood, where the asymptotic and consistent properties are numerically studied as well. The flexibility of this distribution is shown, through an application to a facebook Live-Streaming and Cancer data set. This distribution shows a high efficiency when compared with other one parameter distributions.
The modeling phase of response surface methodology (RSM) involves the application of regression t... more The modeling phase of response surface methodology (RSM) involves the application of regression techniques to fitting a curve to the data generated from a designed experiment. The model-robust regression 2 (MRR2) method is a semi-parametric regression approach that combines portions of estimates from both the parametric and the nonparametric regression approaches via a mixing parameter. However, the robustness of the estimates from the MRR2 approach depends largely on the choice of bandwidth. Utilizing the cross-validation approach to bandwidth selection, we propose a methodology for deriving a data-driven function that generates local bandwidths for the MRR2 approach. Using two examples from the literature and a simulation study, we show that, in comparison with other regression methods, the results obtained from the MRR2 approach utilizing the proposed function offer remarkable improvements in the goodnessof-fit statistics.
Over the past decade, there have been rapid advances in the development of methods for the design... more Over the past decade, there have been rapid advances in the development of methods for the design and analysis of optimal split-plot experiment. Industrial experimentation involving optimality criteria has not been fully exhausted. In this study, we present a literature review on the development of optimal design of split-plot experiments. Split-plot designs, optimality criteria are discussed. Recent developments of optimal split-plot designs is evaluated and compared. Keywords : Optimality, Designs, Experiment, Randomization, Split-plot, Algorithm, Blocks.
The modeling phase of response surface methodology (RSM) involves the application of regression t... more The modeling phase of response surface methodology (RSM) involves the application of regression techniques to fitting a curve to the data generated from a designed experiment. The model-robust regression 2 (MRR2) method is a semi-parametric regression approach that combines portions of estimates from both the parametric and the nonparametric regression approaches via a mixing parameter. However, the robustness of the estimates from the MRR2 approach depends largely on the choice of bandwidth. Utilizing the cross-validation approach to bandwidth selection, we propose a methodology for deriving a data-driven function that generates local bandwidths for the MRR2 approach. Using two examples from the literature and a simulation study, we show that, in comparison with other regression methods, the results obtained from the MRR2 approach utilizing the proposed function offer remarkable improvements in the goodnessof-fit statistics.
Objective: In modeling environment processes, multi-disciplinary methods are used to explain, exp... more Objective: In modeling environment processes, multi-disciplinary methods are used to explain, explore and predict how the earth responds to natural human-induced environmental changes over time. Consequently, when analyzing spatial processes spatial domains, the spatial covariance of interest are always heterogeneous. However, this article proposed locally adaptive covariance for the spatial domain whose covariance is nonstationary in their spatial domain. The objectives of the study are to propose parametric, non-parametric and semi-parametric models for nonstationary spatial structure, continuous model for nonstationary spatial processes whose distance is far apart and to propose the adaptive weighting scheme approach that generates the optimal value for the nonparametric and semi-parametric models. Material and Methods: The spatial covariances are derived by applying the concept of adaptive weighting scheme approach on the covariance proposed in Nott and Dunsmuir (2002). Conseque...
The study introduced an algorithm for generating optimal split-plot designs. The designs were con... more The study introduced an algorithm for generating optimal split-plot designs. The designs were considered as optimal because they were capable and ecient in estimating the xed e ects of the statistical model that is appropriate given the split-plot design structure. Here, we introduced I-optimal design of split-plot experiments. The algorithm used in this research does not require the prior speci cation of a candidate set. Therefore, making the design of split-plot experiments computationally feasible in situations where the candidate set is too large to be tractable. Flexible choice of the sample size, inclusion of both continuous and categorical factors were allowed by this method. We show through an example the substantial bene ts of this method.
This study aims at investigating the satisfaction level of Automated Teller Machine (ATM) users i... more This study aims at investigating the satisfaction level of Automated Teller Machine (ATM) users in a Nigerian University (University of Benin, Benin City, Nigeria: A case study). We observed that there were no differences in the mean knowledge of ATM features among the sex and status of the staff and students (respondents) of the University. The study also revealed that the staff and students of the University are satisfied with the present ATM facilities in the University, but preferred 200 naira notes to the present 500 and 1000 naira notes being dispensed by ATM at various locations in the University. Keywords : Automated Teller Machine, questionnaire, respondent, satisfaction, surcharge, hypothesis.
Over the past decade, there have been rapid advances in the development of methods for the design... more Over the past decade, there have been rapid advances in the development of methods for the design and analysis of optimal split-plot experiment. Industrial experimentation involving optimality criteria has not been fully exhausted. In this study, we present a literature review on the development of optimal design of split-plot experiments. Split-plot designs, optimality criteria are discussed. Recent developments of optimal split-plot designs is evaluated and compared. Keywords : Optimality, Designs, Experiment, Randomization, Split-plot, Algorithm, Blocks.
The study introduced an algorithm for generating optimal split-plot designs. The designs were con... more The study introduced an algorithm for generating optimal split-plot designs. The designs were considered as optimal because they were capable and ecient in estimating the xed e ects of the statistical model that is appropriate given the split-plot design structure. Here, we introduced I-optimal design of split-plot experiments. The algorithm used in this research does not require the prior speci cation of a candidate set. Therefore, making the design of split-plot experiments computationally feasible in situations where the candidate set is too large to be tractable. Flexible choice of the sample size, inclusion of both continuous and categorical factors were allowed by this method. We show through an example the substantial bene ts of this method.
This paper investigates the finite sample performance of power and size properties of several maj... more This paper investigates the finite sample performance of power and size properties of several major co-integration tests using simulation analysis. These tests include; the co-integration Regression Durbin-Watson test (CRDW), Eagle-Granger test, Dicky Fuller unit root test with () statistics, Johansen likelihood ratio tests, and Phillips-Ouliaris test. Comparisons of tests are evaluated based on the proportion of rejects of the hypothesis of a no co-integration. This study answers the question of which co-integration test is better, particularly between the Eagle-Granger two-step test and the Johansen’s tests for co-integration, when the sets of parameters in models are persistence and spiky. The bivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH(1,1)) model with Gaussian innovations, is used in the data generating process (DGP). Our simulation results reveal that there is size distortion in the different co-integration test considered. The Eagle-Granger two-...
International Journal of Scientific & Technology Research, 2013
In this paper we presented the multivariate extension of multiple linear regression using Jackkni... more In this paper we presented the multivariate extension of multiple linear regression using Jackknife techniques in modeling the relationship between m set of responses 1 2 , , , m Y Y Y and a single set of r regressors 1 2 , , , m Z Z Z . The responses are Oil Import 1 ( ), Y Non-Oil Import 2 ( ), Y Oil Export 3 ( ), Y Non-Oil Export 4 ( ) Y which is classified as Nigeria Foreign Trade, while the regressors are Exchange Rate of US Dollar 1 ( ), Z and Exchange Rate of Pounds sterling’s 2 ( ) Z which are classified as Foreign Exchange Rate. We proposed new algorithm for estimating the parameters of multivariate linear regression using the jackknife technique. The results obtained using Jackknife delete-5 algorithm competes favorably with the existing methods. Consequently Time Series approach was adopted for future prediction of the Nigeria Foreign Trade from year 2011 to 2020. Evidently, the time series plot depicts an increase of exchange rate of US Dollar and Pounds Sterling ove...
Communications in Statistics - Theory and Methods, 2017
This paper presents a new criterion for selecting a two-level fractional factorial design. The th... more This paper presents a new criterion for selecting a two-level fractional factorial design. The theoretical underpinning for the criterion is the Shannon entropy. The criterion, which is referred to as the entropy-based minimum aberration criterion, has several advantages. The advantage of the entropy-based criterion over the classical minimum aberration criterion is that it utilises a measure of uncertainty on the skewness of the distribution of word length patterns in the selection of the 'best' design in a family of two-level fractional factorial plans. The criterion evades the trauma associated with the lack of prior knowledge on the important effects.
In this paper, we propose Complementary Kumaraswamy Weibull Power Series (CKWPS) Distributions. T... more In this paper, we propose Complementary Kumaraswamy Weibull Power Series (CKWPS) Distributions. The method is obtained by compounding the Kumaraswamy-G distribution and Power Series distribution on a latent complementary distance problem base. The mathematical properties of the proposed class of distribution are studied. The method of Maximum Likelihood Estimation is used for obtaining the estimates of the model parameters. A member of the family is investigated in detail. Finally an application of the proposed class is illustrated using a real data set.
Journal of Modern Applied Statistical Methods, 2014
Model-Robust Regression 2 (MRR2) method is a semi-parametric regression approach that combines pa... more Model-Robust Regression 2 (MRR2) method is a semi-parametric regression approach that combines parametric and nonparametric fits. The bandwidth controls the smoothness of the nonparametric portion. We present a methodology for deriving data-driven local bandwidth that enhances the performance of MRR2 method for fitting curves to data generated from designed experiments.
This paper proposes an algorithm for the estimation of the parameters of logistic regression anal... more This paper proposes an algorithm for the estimation of the parameters of logistic regression analysis using Jackknife. Jackknife delete-one and deleted algorithm was used to provide estimates of logistic regression coefficient. The Jackknife standard deviation provides an estimate of variability of the standard deviation of sample and it is a good measure of precision. The method was illustrated with real life data; and the results obtained from the Jackknife samples was compared with the result from ordinary logistic regression using the maximum likelihood method and results obtained reveals that the values from the jackknife algorithm for the parameter estimation, standard deviation and confidence interval were so close to the result from ordinary logistic regression analysis, this provides a good approximation to the result which shows that there is no bias in the jackknife coefficients.
This paper proposes an algorithm for the estimation of the parameters of logistic regression anal... more This paper proposes an algorithm for the estimation of the parameters of logistic regression analysis using Jackknife. Jackknife delete-one and deleted algorithm was used to provide estimates of logistic regression coefficient. The Jackknife standard deviation provides an estimate of variability of the standard deviation of sample and it is a good measure of precision. The method was illustrated with real life data; and the results obtained from the Jackknife samples was compared with the result from ordinary logistic regression using the maximum likelihood method and results obtained reveals that the values from the jackknife algorithm for the parameter estimation, standard deviation and confidence interval were so close to the result from ordinary logistic regression analysis, this provides a good approximation to the result which shows that there is no bias in the jackknife coefficients.
American Journal of Mathematics and Statistics, 2012
We constructed an) (2 s E-optimal supersaturated design (SSD) with an experimental run-size, n = ... more We constructed an) (2 s E-optimal supersaturated design (SSD) with an experimental run-size, n = 20 and number of factors, m = 57 (mu ltip le of 19). The construction is based on balanced incomplete block designs using a theorem proposed by Bulutoglu and Cheng. This is achieved by constructing the initial b locks of the balanced inco mplete block design using the theorem. Consequently, all other blocks are generated to constitute a balanced incomplete block design (BIBD),and the complete blocks that constitute the BIBD is transformed into the required supersaturated design(SSD).
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Papers by Julian Mbegbu