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Analyzing the Economic Development Using Partial Least Square Structural Model: A Case of Narok, Kenya
Otieno Okumu Kevin,
Samuel Muthiga Nganga
Issue:
Volume 9, Issue 2, April 2021
Pages:
33-43
Received:
18 December 2020
Accepted:
25 December 2020
Published:
17 March 2021
Abstract: After the establishment of the Narok County government and the transition from the central system of government into the Devolved system of governance, majority of the residents of Narok County had much anticipation in terms of developments that will take place as a result of governance being brought close to them. The study was checking economic development changes that has taken place in Narok Town the Headquarter of Narok County since the establishment of the Narok County Government. The objective was to access how the introduction of county government has impacted on the economic development by investigating its impact on the various key indicators of the economic development such as health, trade, and infrastructure. The study used a sample of 320 residents drawn at random from all parts of the town, the samples was surveyed using a written survey instrument and their opinion on the state of various economic indicators was captured and used to develop a structural equation model using SmartPLS 3 software, in order to use in examining the economic development status of Narok Town. The study fits a significant model that can tell the whereabouts of the economic status of the Town presently and in future. It was concluded that the county government has not done much in terms of economic development since the introduction of County government because the rural areas in the county are still struggling to catch up with the indicators of economic development. It was also evidenced that the impact of County government on trade is good compared to its impact on health and infrastructure.
Abstract: After the establishment of the Narok County government and the transition from the central system of government into the Devolved system of governance, majority of the residents of Narok County had much anticipation in terms of developments that will take place as a result of governance being brought close to them. The study was checking economic d...
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Estimating the Parameters of (POGE-G) Distribution and Its Application to Egyptian Mortality Rates
Abeer Mohamed,
Amira Elghany,
Gamalat Elgabry
Issue:
Volume 9, Issue 2, April 2021
Pages:
44-56
Received:
1 March 2021
Accepted:
17 March 2021
Published:
30 March 2021
Abstract: In this paper, we consider power odd generalized exponential-Gompertz (POGE-G) distribution which is capable of life tables to calculate death rates (failure). Based on simulated data from the PPOGE-G distribution, we consider the problem of estimation of parameters under classical approaches and Bayesian approaches. In this regard, we obtain maximum likelihood (ML) estimates, maximum product of spacing (MPS) and Bayes estimates under squared error loss function. We also compute 95% asymptotic confidence interval and highest posterior density interval estimates. The Monte Carlo simulation will be conduct to study and compare the performance of the various proposed estimators (simulation study indicates that the performance of MPS estimates is better MLE estimates and the performance of Bayes estimates is also better). Finally, application of a real data from the projections of the future population for the total of the Egyptian Arabic Republic for the period 2017-2052, depending on the book which introduced from the central agency for public mobilization and statistics in Feb (2019) from this application it could be said that this distributions can be applied to mortality rate data set. The present paper can also be extended to design of progressive censoring sampling plan and other censoring schemes can also be considered.
Abstract: In this paper, we consider power odd generalized exponential-Gompertz (POGE-G) distribution which is capable of life tables to calculate death rates (failure). Based on simulated data from the PPOGE-G distribution, we consider the problem of estimation of parameters under classical approaches and Bayesian approaches. In this regard, we obtain maxim...
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A Comparison of the Lehmann and GLM ROC Models
Melissa Innerst,
Jack D. Tubbs,
Musie Ghebremichael
Issue:
Volume 9, Issue 2, April 2021
Pages:
57-72
Received:
8 December 2020
Accepted:
25 March 2021
Published:
7 May 2021
Abstract: Recently, several regression methods have been developed to model the receiver operating characteristic curve (ROC), as a measure of accuracy for potential biomarker use in diagnostic testing and disease detection. In this paper, we investigate the Lehmann ROC regression model and compare it to more commonly used ROC regression methods that are found in the literature. The comparative performance of the methods are evaluated using simulated data from the normal, extreme value, and the Weibull distributions. Theory suggests that the Lehmann method should only work well when using the Weibull distribution. Our simulation results suggest that the performance of these methods is more complicated than the theory might suggest. The methods were demonstrated using data from a study concerning the clinical effectiveness of leukocyte elastase determination in the diagnosis of coronary artery disease (CAD).
Abstract: Recently, several regression methods have been developed to model the receiver operating characteristic curve (ROC), as a measure of accuracy for potential biomarker use in diagnostic testing and disease detection. In this paper, we investigate the Lehmann ROC regression model and compare it to more commonly used ROC regression methods that are fou...
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