by Caspah Lidiema, Anthony Waititu, Thomas Mageto and Anthonyn Ngunyi
Original Research
Generalized Additive Models for Location, Scale and Shape (GAMLSS)is a very flexible model class, extending the classical Generalized Additive Model (GAM) framework. Not only the mean, but all distribution parameters are regressed to the predictors. It is suitable for fitting linear or non-linear parametric models using the distributions. Artificial Neural Networks (ANN) are biologically inspired computer programs designed to simulate the way in which the human brain processes information. ANNs gather their knowledge by detecting the patterns and relationships in data and learn (or are trained) through experience. The main advantages of using ANN is that, it has the ability to implicitly detect complex nonlinear relationships between dependent and independent variables and also has ability to detect all possible interactions between predictor variables. Given all the dynamic nature of these two models are their outlined merits, it’s important to test and see which of this model estimates parameters better and which of them a better model in forecasting financial data. To test and compare this models an application of effect remittances on household credit was be used. The study employed monthly data for period January 2005- December 2017 in Kenya. Our findings showed that mixed results where, GAMLSS performed better than ANN in estimation while ANN provided a better model in prediction than GAMLSS. Our results confirm that the surge in Remittances leads to increase credit uptake due to increased resource mobilization by financial institutions and also resource availability for loan repayment. The research recommends Banks and Financial institutions should also carry out their assessment using GAMLSS and ANN and come up with ways of tapping into remittances not only to boost their deposits but also increase their funds for issuing credit and hence increase interest income, and also boost financial inclusion in Kenya through increased consumer loans.
American Journal of Applied Mathematics and Statistics. 2018, 6(1), 25-35. DOI: 10.12691/ajams-6-1-5
Pub. Date: March 31, 2018
12971 Views2688 Downloads
by Caspah Lidiema, Anthony Waititu, Thomas Mageto and Anthonyn Ngunyi
Original Research
This research paper use Bayesian VAR framework to forecast the household credit in the dynamic market of foreign remittances inflow to Kenya. The Bayesian VARs model in this study employs the sims-Zha prior to estimate. Bayesian vector autoregressive (BVAR) uses Bayesian methods to estimate a vector autoregressive (VAR). In that respect, the difference with standard VAR models lies in the fact that the model parameters are treated as random variables, and prior probabilities are assigned to them. This study employed data from the Kenyan Market for the period January 2005-December 2017. The forecast results were compared with the standard ARIMA model and the findings confirm that the BVAR approach outperforms the ARIMA model. Financial institutions can therefore use Bayesian VAR and other Bayesian models in predicting credit uptake given several micro-economic conditions. Banks should also find ways of tapping into these remittances especially those that pass through informal channels to improve their earnings from processing fees and also enhance the financial inclusion agenda through increasing account opening and loan uptake.
American Journal of Applied Mathematics and Statistics. 2018, 6(1), 17-24. DOI: 10.12691/ajams-6-1-4
Pub. Date: March 28, 2018
11351 Views2574 Downloads
by Mohamed E. M. Abdelhafez
Original Research
The main objective of this paper is to investigate the impact of diabetes on the psychological characteristics in children. The study investigated 302 children aged 7 to 13 years old who had diabetes type I in Kuwait. A questionnaire was administered to participants (Parents or Guardians) of diabetic children. The questionnaire has two parts; the first part has sociodemographic and clinical characteristics of the children and participants and the second part is the "strengths and difficulties questionnaire" (SDQ) [1]. The strengths and difficulties questionnaire (SDQ) was widely used for screening emotional and behavioral problems. Internal consistency of the sample and the strengths and difficulties questionnaire (SDQ) (Arabic version) were measured by Cronbach's alpha coefficient. The percentages of children whose scores are in the normal, borderline, and abnormal classes were calculated. The results indicate that regarding the mental health of the children, 69.1% were considered positive overall (55% abnormal and 14.1% borderline). Correlation analysis on the item-subscale level revealed that all items had the highest correlations to their respective subscales of origin. Further, subscale-subscale and subscale-total correlations were calculated. The results show significant correlations between the five subscales of the SDQ. Each subscale correlated significantly (p < 0.01) with every other subscale. A principal component analysis with varimax rotation was conducted to investigate the factorial structure of scales. A discriminant analysis was performed to classify the diabetic children into one of the three groups (Normal, borderline, and abnormal). The results show that 93.3% of the original grouped cases were correctly classified.
American Journal of Applied Mathematics and Statistics. 2018, 6(1), 9-16. DOI: 10.12691/ajams-6-1-3
Pub. Date: March 19, 2018
10993 Views2698 Downloads
by K. Prudhvi
Original Research
In this paper, we study a unique common fixed point theorem for four self mappings in dislocated metric spaces, which generalizes, extends and improves some of the recent results existing in the literature.
American Journal of Applied Mathematics and Statistics. 2018, 6(1), 6-8. DOI: 10.12691/ajams-6-1-2
Pub. Date: February 26, 2018
8253 Views2270 Downloads
by N. Priyobarta, Yumnam Rohen and Stojan Radenovic
Original Research
In this paper, we introduce the notion of parametric A-metric space as generalisation of parametric metric space and parametric S-metric space. Further we prove some fixed point theorem of expansive mapping in the setting of parametric A-metric space.
American Journal of Applied Mathematics and Statistics. 2018, 6(1), 1-5. DOI: 10.12691/ajams-6-1-1
Pub. Date: January 19, 2018
8044 Views2477 Downloads