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On Order and Regime Determination of SETAR Model in Modelling Nonlinear Stationary Time Series Data Structure: Application to Lafia Rainfall Data, Nasarawa State, Nigeria
Nicholas Pindar Dibal,
Akeyede Imam,
Mustafa Babagana Abubakar
Issue:
Volume 10, Issue 2, March 2021
Pages:
89-98
Received:
9 January 2021
Accepted:
16 January 2021
Published:
3 March 2021
Abstract: The linear time series model refers to the class of models for which fixed correlation parameters can fully explain the dependency between two random variables, but many real-life circumstances, such as monthly unemployment results, supplies and demands, interest rate, exchange rate, share prices, rainfall, etc., violate the assumption of linearity. For fitting and forecasting of nonlinear time series data, the self-exiting threshold autoregressive (SETAR) model was suggested. Using R to generate random nonlinear autoregressive data, a Monte Carlo simulation was performed, the SETAR model was fitted to the simulated data and Lafia rainfall data, Nasarawa State, Nigeria to determine the best regime orders and/or scheme number to make future forecast. Using Mean Square Error (MSE) and Akaike Information Criteria (AIC), the relative performance of models was examined. At a specific autoregressive order, regime order, sample size and step ahead, the model with minimum criteria was considered as the best. The results show that the best autoregressive and regime orders to be chosen are 3rd and 2nd [SETAR (3, 2)] respectively for fitting and forecasting nonlinear autoregressive time series data with small and moderate sample sizes. As the sample size increases, the output of the four models increases. Finally, it is shown that when sample size and number of steps forward are increased, the efficiency and forecasting capacity of the four models improves.
Abstract: The linear time series model refers to the class of models for which fixed correlation parameters can fully explain the dependency between two random variables, but many real-life circumstances, such as monthly unemployment results, supplies and demands, interest rate, exchange rate, share prices, rainfall, etc., violate the assumption of linearity...
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Modelling Predictors of Weight Gain of Children Under-Five
Hussein Salifu,
Nyemekye Gabriel,
Isaac Zingure
Issue:
Volume 10, Issue 2, March 2021
Pages:
99-110
Received:
15 February 2021
Accepted:
1 March 2021
Published:
17 March 2021
Abstract: This study examined the determinants of weight gain by children less than five years in the Kintampo municipality of the Bono East Region of Ghana using multivariate analysis of variance (MANOVA) procedure and profile analysis. The study revealed that the minimum weight gain at the first month for males and females are 1.8kg and 1.6kg respectively and that mean weights gain by children under five years was not the same across feeding type. Profile plots of main effect revealed that baby’s age group 0-6, Exclusive Breast Feeding (EBF), parity levels 6, 7 and mothers who were formally employed are associated with lower mean effects since they fall below the average mean weight. However, child age group 13-18, breast milk substitute and parity 7 are above the average mean weight line of 7.5, indicating significant effect. Interaction plots indicated that the relationship between parity, mother’s age group, employment type and weight depend on other predictor variables. Parity depends on mother’s age but mother’s age does not depend on the child age group with respect to weight gain. Also, employment type neither depend on religion nor child age group but it depends on educational level with respect to weight gain. The MANOVA results showed that feeding type, parity and child age are the influential factors in determining the weight gain of children less than five years. Further, the study revealed that there exists some relationship between feeding type and mother’s education, parity and mother’s age group and between occupation and mother’s age group with respect to weight gain confirming the profile results. It is therefore recommended that nursing mothers should be encouraged to feed their children themselves since feeding practice has a great influence in the growth of the child at the infant stage.
Abstract: This study examined the determinants of weight gain by children less than five years in the Kintampo municipality of the Bono East Region of Ghana using multivariate analysis of variance (MANOVA) procedure and profile analysis. The study revealed that the minimum weight gain at the first month for males and females are 1.8kg and 1.6kg respectively ...
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Poisson Ridge Regression Estimators: A Performance Test
Etaga Harrison Oghenekevwe,
Aforka Kenechukwu Florence,
Awopeju Kabiru Abidemi,
Etaga Njideka Cecilia
Issue:
Volume 10, Issue 2, March 2021
Pages:
111-121
Received:
27 February 2021
Accepted:
15 March 2021
Published:
30 March 2021
Abstract: In Multiple regression analysis, it is assumed that the independent variables are uncorrelated with one another, when such happen, the problem of multicollinearity occurs. Multicollinearity can create inaccurate estimates of the regression coefficients, inflate the standard errors of the regression coefficients, deflate the partial t-tests for the regression coefficients, give false p-values and degrade the predictability of the model. There are several methods to get rid of this problem and one of the most famous one is the ridge regression. The purpose of this research is to study the performance of some popular ridge regression estimators based on the effects of sample sizes and correlation levels on their Average Mean Square Error (AMSE) for Poisson Regression models in the presence of multicollinearity. As performance criteria, average MSE of k was used. A Monte Carlo simulation study was conducted to compare performance of Fifty (50) k estimators under four experimental conditions namely: correlation, Number of explanatory variables, sample size and intercept. From the results of the analysis as summarized in the Tables, the MSE of the estimators performed better in a lower explanatory variables p and an increased intercept value. It was also observed that some estimators performed better on the average at all correlation levels, sample sizes, intercept values and explanatory variables than others.
Abstract: In Multiple regression analysis, it is assumed that the independent variables are uncorrelated with one another, when such happen, the problem of multicollinearity occurs. Multicollinearity can create inaccurate estimates of the regression coefficients, inflate the standard errors of the regression coefficients, deflate the partial t-tests for the ...
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Bayesian Hierarchical Estimation and Impact Analysis of Generalized Production Functions
Xinping Yang,
Wei Zheng,
Yunyuan Yang,
Yanmei Li
Issue:
Volume 10, Issue 2, March 2021
Pages:
122-128
Received:
19 March 2021
Accepted:
30 March 2021
Published:
12 April 2021
Abstract: Bayesian model is constructed to estimate the missing data of capital stock, and the impact of three industrial structures on the tertiary industry is discussed. The results show that: the maximum MC error with missing data on capital stock estimated by Bayesian is 0.4963, the maximum MC error of production function estimated by Bayesian stratation is 0.3276, the standard deviation is 0.0890 and the accuracy is high; from 1993 to 2018, the sum of capital output elasticity and labor output elasticity in the tertiary industry in Yunnan Province was greater than 1, and the scale compensation was increasing; the level of technological progress, the growth rate of all factors, the elasticity of capital output and the elasticity of labor output were all close to stable, and the ranges of changes were 0.2714-0.3252, -0.0680-0.0390, 0.5615-0.5858 and 0.4522-0.4784, respectively; the elasticity of capital output was greater than that of labor force output, and the tertiary industry in Yunnan Province was more dependent on the elasticity of capital output.
Abstract: Bayesian model is constructed to estimate the missing data of capital stock, and the impact of three industrial structures on the tertiary industry is discussed. The results show that: the maximum MC error with missing data on capital stock estimated by Bayesian is 0.4963, the maximum MC error of production function estimated by Bayesian stratation...
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Waiting Time Before Justice in the Law Sector: A QUEUEING Theory
Etaga Harrison Oghenekevwe,
Chikwendu Peace,
Awopeju Kabiru Abidemi,
Aforka Kenechukwu Florence,
Etaga Njideka Cecilia
Issue:
Volume 10, Issue 2, March 2021
Pages:
129-135
Received:
15 March 2021
Accepted:
9 April 2021
Published:
16 April 2021
Abstract: The legal system in Nigeria is be-deviled with delayed justice which has become a source of concern to many person. This is very much peculiar to those who feel that the judiciary is too slow in resolving legal issues in Nigeria. In Nigeria, there abound court cases especially those of criminal dimensions that have ongoing for years now without reaching a conclusive conclusion. The study is aimed at modelling the queuing system in the magistrate courts in Onitsha Magisterial districts. The specific objectives include: to apply the M/M/2 and M/M/3 models with identical and parallel queues to criminal cases in the Magistrate court and to compare the efficiency of the two models and in either cases to determine time to justice in criminal cases in the Magisterial District. The results of the study show that M/M/2 model with 2 identical and parallel queues have an expected number of cases in the system as 39 with 50% idle time while the M/M/3 model with 3 identical and parallel queues have an expected number of cases in the system as 23 cases with 64.88% idle time. The comparison of the two models shows M/M/2 with 2-identical and parallel queues is more efficient as it has more number of cases to attend to and less idle time. The study therefore concludes that the delays in the disposal of cases especially those with criminal nature may not be attributable to the queuing systems in place. Even though lesser number of servers is seen to be efficient, this may not be advised. Increasing the number of servers though will increase speed of disposal of cases, may also lead to increased idle time of servers. As more courts being set up may result in waste of resources, manpower and time as the 2-server system is efficient in speeding up justice delivery in the magisterial division.
Abstract: The legal system in Nigeria is be-deviled with delayed justice which has become a source of concern to many person. This is very much peculiar to those who feel that the judiciary is too slow in resolving legal issues in Nigeria. In Nigeria, there abound court cases especially those of criminal dimensions that have ongoing for years now without rea...
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