Mathematical Theory and Modeling
http://www.iiste.org/Journals/index.php/MTM
<p><span id="internal-source-marker_0.04939836589619517"><span id="internal-source-marker_0.04939836589619517">Mathematical Theory and Modeling </span>is a peer reviewed journal published by IISTE. The journal publishes original papers at the forefront of mathematical theories, modelings, and applications. The journal is published in both printed and online versions. The online version is free access and download.</span></p><p><span>IISTE is member of <a href="http://www.crossref.org/01company/17crossref_members.html">CrossRef</a>.<br /></span></p>en-USMathematical Theory and Modeling2224-5804A Study On (H, 1)(E, q) Product Summability Of Fourier Series And Its Conjugate Series
http://www.iiste.org/Journals/index.php/MTM/article/view/37213
<p><em>In this paper, introduce the concept of (H,1) (E,q) product operators and establishes two new theorems on (H,1)(E,q) product Summability of Fourier series and its conjugate series. The results obtained in the paper further extend several known result on linear operators.</em></p> <strong><em>Keyword: </em></strong><em>(E,q) Summability, (H,1) Summability, (H,1) (E,q) Summability</em>Sheela Verma7Bayesian Panel Data Model Based on Markov Chain Monte Carlo
http://www.iiste.org/Journals/index.php/MTM/article/view/37214
<p>The general aim of this paper is to deal with problems of estimation , prediction, and model building for panel data model .Bayesian approach based on Markov chain Monte Carlo (MCMC) employed to make inferences on panel data model coefficients under some conditions on the prior distribution . We investigate the posterior density and identify the analytic form of the Bayes factor for checking the model.</p> <p> </p> <p><strong>Keywords: </strong>Panel Data Model , Likelihood function , Bayesian approach , Markov chain Monte Carlo (MCMC), Prior distribution, Posterior distribution , Bayes factor.</p>Ameera Jaber MohaisenSaja Yaseen Abdulsamad7QUEUING CHARACTERISTICS OF THE DENTAL DEPARTMENT AT ESSIKADO HOSPITAL
http://www.iiste.org/Journals/index.php/MTM/article/view/37215
<p>In this paper, the queuing characteristics at the dental department of Essikado Hospital in the Sekondi-Takoradi Metropolis was analysed using a Single-server queuing Model. The data was collected over a period of one week, from 8:30am-11:30 am each day.</p> <p>By using the queuing rule First-come, First-served as practiced by the case study and M/M/s queuing model, the performance measures were calculated. The average/mean arrival and mean service times were found to be 1.6 patients/hour and 4.4477 patients/hour respectively. The average number of patients in the system and in the queue was 0.5619 patients and 0.2021 patients respectively. Also, the average time spent in the system and the average time it takes for service to start was 0.3512 hours and 0.1263 hours respectively.</p> <p>The paper recommends the need to obtain a central tray setup system for instruments required for the different dental procedures so as to reduce the time spent in sorting them up thereby reducing the amount of time spent in queue. It also respectfully submits a suggestion on the need to increase the number of dentist from one to two.</p> <p><strong>Keywords: </strong>Essikado Hospital; Queuing characteristics; First-come, First- served; Single-server Model; Utilization Factor; M/M/s Queuing Model; Mean Arrival Rate; and mean Service Rates.</p>Rebecca Nduba ArhinSarah-Lynn MensahEmile Kpakpo Adotey7Effect of magnetic field on peristaltic flow of Williamson fluid through a porous medium in an inclined tapered asymmetric channel.
http://www.iiste.org/Journals/index.php/MTM/article/view/37216
<p>Effects of magnetic field on peristaltic flow of Williamson fluid through a porous medium as well as effects of non-slip and heat transfer are considered in an inclined tapered asymmetric channel. The problem is studied under long wave length and low Reynolds number assumption, the perturbation technique is used to solve the problem as the equations are non linear. The stream function, the temperature distribution and the pressure rise are calculated. The effect of various parameter on the pumping characteristic and on the temperature profiles as well as stream functions and velocity profiles are discussed with the help of graphs.</p> <p><strong>Keywords</strong>: Williamson fluid, Peristaltic transport, magnetic field, porous medium , non-slip effects, heat transfer, an inclined tapered asymmetric channel.</p>Ahmed M. AbdulhadiTamara S. Ahmed7Modeling Cassava Yield In Western Kenya: Optimal Scaling Integrated With Principal Component Regression Approach
http://www.iiste.org/Journals/index.php/MTM/article/view/37217
<p>Cassava is a major food crop grown in the tropical and subtropical parts of the world. In this research work, we sought to develop a model for predicting cassava yield using the PCR model integrated with optimal scaling. Moreover, establishing relationship between the different factors of production, estimate the yield based on the key components adduced to the factors of production in trial data in Western region, Kenya. Principal component analysis and optimal scaling were used. Pearson correlation prior to principal component analysis indicated significance correlation among the factors of production. A prior to principal component regression, analysis using the variance inflation factor also indicated correlation in key factors of yield forecasting, VIF of 1666.667 (<em>R</em><sup>2</sup>=0.999). The coefficients derived from this model were unstable and therefore not reliable for yield prediction .Using the amount of explained variance criterion (70%-80%), we selected the first eight principal components which accounted for almost 70% of total model variance. Eight (8) key components were obtained as key determinants of yield; the most vital component having an eigen value of 2.149 and the least important having an eigen value of 1.005. The post principal component regression model was fitted. The PCR model indicated non-correlation among the eight principal components with the VIF attributed to the overall PCR model being 2.564, (<em>R</em><sup>2</sup>=0.610 (Adj <em>R</em><sup>2</sup>=0.590). The model offers an efficient alternative to existing models for crop yield prediction when the number of factors to be included in the model is high.</p> <p><strong>Keywords</strong>: PCR, PCA, VIF</p>Vincent Alulu HarryGeorge OrwaHenry Athiany7Modelling Rates of Inflation in Kenya: An Application of Garch and Egarch Models
http://www.iiste.org/Journals/index.php/MTM/article/view/37218
<p>The purpose of this study was to determine an effective Arch-type model for forecasting Kenya’s inflation. Using Kenya monthly inflation data from January 1990 to December 2015, the performance of GARCH and EGARCH type models was analyzed to come up with the best model for forecasting Kenyan inflation data. Since the inflation series is non-stationary, the Consumer Price Index (CPI) was first transformed to return series by logarithmic transformation. Afterwards, the data was tested for the presence of ARCH effects and serial correlation using both Ljung Box Pierce Q test and Engle Arch test. The test showed presence of heteroscedasticity and correlation in the inflation return series which is a key feature of a financial time series data. The project adopted AIC and BIC in selecting the the best model. From the fitted models EGARCH (1,1) had the smallest AIC and BIC values followed by the GARCH(1,1) model. Model diagnostic test was conducted on the selected model EGARCH (1,1) model to determine its adequacy and goodness of fit. QQ plot was fitted to the residuals of the model and fairly straight line was produced looking roughly linear. Furthermore weighted Ljung Box Test on standard squared residuals showed the absence of correlation in the model. In conclusion, EGARCH(1,1) model is the best model for forecasting Kenyan inflation data.</p> <p><strong>Keywords: </strong>AIC, BIC, Model adequacy and heteroscedasticity</p>Sammy Oketch FwagaGeorge OrwaHenry Athiany7A Non-standard discrete model for the solution of first order Ordinary Differential Equations using minimally characterized interpolating function
http://www.iiste.org/Journals/index.php/MTM/article/view/37219
<p>We present a new set of one step finite difference schemes for the numerical solution of First order differential equations using a combination of an interpolation function and a modification of the resulting schemes by replacing step size with a suitable function of as required by the second non-standard modeling rule. The resulting schemes have been applied to some initial value problems and the schemes have been found to possess desirable qualitative properties.</p> <p><strong>KEYWORDS</strong></p> <p><strong> </strong> Nonstandard methods, Hybrid, Interpolation functions, Non-standard modeling rules, Standard Finite difference methods<em></em></p>Obayomi A. A.Ayinde S.O7