Showing papers in "Mathematical theory and modeling in 2014"

Transmuted Inverse Rayleigh Distribution: A Generalization of the Inverse Rayleigh Distribution.

Abstract: In this article, we generalize the Inverse Rayleigh distribution using the quadratic rank transmutation map studied by Shaw et al. (2007) to develop a transmuted inverse Rayleigh distribution. The properties of this distribution are derived and the estimation of the model parameters is performed by maximum likelihood method. Keywords: Inverse Rayleigh Distribution, Transmutation Map, Hazard Rate Function, Reliability Function, Order Statistics, Parameter Estimation.

Time Series Forecasting of Solid Waste Generation in Arusha City - Tanzania

Abstract: Statistical time series modeling is widely used in prediction and forecasting studies. This study intends to analyze, compare and select the best time series model for forecasting amount of solid waste generation for the next years in Arusha city - Tanzania among ARMA/ARIMA and Exponential Smoothing models. The past data used are monthly amount of solid waste collected by the city authorities from year 2008 to 2013. The result indicated that ARIMA (1, 1, 1) outperformed other potential models in terms of MAPE, MAD and RMSE measures and hence used to forecast the amount of the solid waste generation for the next years. Keywords: ARIMA models, Exponential Smoothing models, time series, MAPE, MAD, RMSE

A Multi-Stage Supply Chain Network Optimization Using Genetic Algorithms

Abstract: In today's global business market place, individual firms no longer compete as independent entities with unique brand names but as integral part of supply chain links. Key to success of any business is satisfying customer's demands on time which may result in cost reductions and increase in service level. In supply chain networks decisions are made with uncertainty about product's demands, costs, prices, lead times, quality in a competitive and collaborative environment. If poor decisions are made, they may lead to excess inventories that are costly or to insufficient inventory that cannot meet customer's demands. In this work we developed a bi-objective model that minimizes system wide costs of the supply chain and delays on delivery of products to distribution centers for a three echelon supply chain. Picking a set of Pareto front for multi-objective optimization problems require robust and efficient methods that can search an entire space. We used evolutionary algorithms to find the set of Pareto fronts which have proved to be effective in finding the entire set of Pareto fronts. Key words: multi-objective optimization, Pareto fronts, evolutionary algorithms, supply chain networks, echelon.

Climatic Effects on Cotton and Tea Productions in Bangladesh and Measuring Efficiency using Multiple Regression and Stochastic Frontier Model Respectively

Abstract: The main objective of this study is to develop Multiple Regression model to measure the Climatic effects on cash crop (Cotton and Tea) productions and to measure productions efficiency due to Climates using Stochastic Frontier model From the analysis of the Multiple Regression model which gives the high R-square value implies to accept a good model At the same time, all other assumptions and model validation checking test are very well satisfied which implies these fitted model are good model to measure the climatic effects in Bangladesh Again, From the Stochastic Frontier model, there is a huge opportunity to increase Cotton production by increasing Technology to get maximum productions and Tea achieves maximum productionsKey words: Cash crop, Climate, Multiple Regression model and Stochastic Frontier model

Numerical Solution of Linear Volterra-Fredholm Integral Equations Using Lagrange Polynomials

Abstract: In this paper, new algorithms for finding numerical solution of Linear Volterra-Fredholm integral equations (LVFIE's) of the second kind are introduced. The methods based upon Lagrange polynomial approximation, Barycentric Lagrange polynomial approximation, and Modified Lagrange polynomial approximation. Also, some examples are included to improve the validity and applicability of the techniques. Finally a comparison between the proposed methods and other methods were used to solve this kind of equations.

Mhd thermal stagnation point flow towards a stretching porous surface

Abstract: This paper presents an investigation of the hydromagnetic stagnation flow of an incompressible viscous, electrically conducting fluid, towards a stretching sheet in the presence of axially in- creasing free stream velocity. The Newton-Raphson shooting method along with the fourth-order Runge-Kutta integration algorithm has been employed to tackle the third order, nonlinear boundary layer equation governing the problem. The results indicate that suction and thermal Grashof number have the same effect on the rate of heat transfer. The magnetic parameter has the effect of increasing the skin friction coefficient whilst the reverse is observed for increasing the velocity ratio parameter. Keywords: Convective flow, Viscous, MHD, Free stream, Stagnation Point, Suction, Velocity Ratio

Effects of wall properties and heat transfer on the peristaltic transport of a jeffrey fluid through porous medium channel

Abstract: A mathematical model is constructed to study the effect of heat transfer and elasticity of flexible walls with porous medium in swallowing of food bolus through the oesophagus. The food bolus is supposed to be Jeffrey fluid and the geometry of wall surface of oesophagus is considered as peristaltic wave through porous medium. The expressions for temperature field, axial velocity, transverse velocity and stream function are obtained under the assumptions of low Reynolds number and long wavelength. The effects of thermal conductivity, Grashof number, Darcy number, magnet, rigidity, stiffness of the wall and viscous damping force parameters on velocity, temperature and stream function have been studied. It is noticed that increase in thermal conductivity, Darcy number, Grashof number and the Jeffrey parameter results in increase of velocity distribution. It is found that the size of the trapped bolus increases with increase in the Jeffrey parameter, rigidity and stiffness. Keywords ­: Magnetohydrodynamic, Peristaltic transport, Oesophagus, Jeffrey fluid, Porous medium, Food bolus.

New Proposed Length-Biased Weighted Exponential and Rayleigh Distribution with Application

Abstract: The concept of length-biased distribution can be employed in development of proper models for lifetime data. Length-biased distribution is a special case of the more general form known as weighted distribution. In this paper we introduce a new class of length-biased of weighted exponential and Rayleigh distributions(LBW 1 E 1 D), (LBWRD).This paper surveys some of the possible uses of Length - biased distribution We study the some of its statistical properties with application of these new distribution . Keywords : length- biased weighted Rayleigh distribution, length- biased weighted exponential distribution, maximum likelihood estimation.

A comparative study of initial basic feasible solution methods for transportation problems

Abstract: In this research three methods have been used to find an initial basic feasible solution for the balanced transportation model. We have used a new method of Minimum Transportation Cost Method (MTCM) to find the initial basic feasible solution for the solved problem by Hakim [2]. Hakim used Proposed Approximation Method (PAM) to find initial basic feasible solution for balanced transportation model and then compared the results with Vogel’s Approximation Method (VAM) [2]. The results of both methods were noted to be the same but here we have taken the same transportation model and used MTCM to find its initial basic feasible solution and compared the result with PAM and VAM. It is noted that the MTCM process provides not only the minimum transportation cost but also an optimal solution.

The Continuous Classical Optimal Control of a Coupled of Nonlinear Elliptic Equations

Abstract: This paper is concern with the existence and the uniqueness solution of the state vector of a couple of nonlinear elliptic partial differential equations for a given continuous classical control vector. Also the existence theorem of a continuous classical optimal control vector governing by the considered couple of nonlinear partial differential equation of elliptic type with equality and inequality constraints is developed and proved. The existence and the uniqueness solution of the couple of adjoint equations associated with the considered couple equations of the state is studded. The derivation of the Frcehet derivative of the Hamiltonian is obtained. The necessary conditions theorem so as the sufficient conditions theorem of optimality of the constrained problem are developed and proved. Keywords: Classical optimal control, system of nonlinear elliptic, necessary and sufficient conditions.

On the Selection of Samples in Probability Proportional to Size Sampling: Cumulative Relative Frequency Method

Abstract: Generally in the sense that, the unit with large size contain more ancillary information than the unit with smaller size. So when samples from different sized subgroups or units are used and sampling is taken with the same probability, the chances of selecting a member from a large group are less than selecting a member from a smaller group although here the chances of selecting a member from a large group will be greater than selecting a member from a smaller group. That is it is clear that, the probability of selecting a unit is positively proportional to its size. The aim of this paper is to propose a method of selecting samples in probability proportional to size. This method uses relative frequency to select samples in probability proportional to size. Comparatively it takes less time and easy to apply than Cumulative Total Method and Lahiri’s Method. Keywords: Probability Proportional to Size (PPS) Sampling, Cumulative Total Method, Lahiri’s Method, Cumulative Relative Frequency Method.

Mathematical Formulation Model for a School Bus Routing Problem with Small Instance Data

Abstract: This paper aims to describe the mathematical formulation model and an exact optimal solution analyses for a school bus routing problem with small instance data. The formulated model has been used to compute the optimal solution of time spent by students at all bus stops, apart from that the bus stops are not necessary be linearly ordered. We also listed down five procedures of mathematical formulation model to reach an exact optimal solution for a school bus routing problem with small instance data. We assume that each bus has fixed pick up points, these generates the many possible routes for a bus, the number of routes that generated is equal to permutation of pick up points, for each route of a bus we computing the objective function and the route with smallest objective function value can be optimal route of a bus. The sample data from two schools located at Dar es Salaam are collected and validated in the model to shows the good performing of that model. The optimal solution results obtained shows that the students spent minimal minutes in new planned routes compared to current routes. Keywords: bus stop, students, buses, optimal value, optimal solution, set, pick up.

On the product and ratio of pareto and kumaraswamy random variables

Abstract: The distributions of the product XY and the ratio X/Y are derivedwhen X and Y are Pareto and the Kumaraswamy random variablesdistributed independently of each other.

Simulation of A Mathematical Model Of Hepatitis B Virus Transmission Dynamics In The Presence Of Vaccination And Treatment

Abstract: In this paper, a mathematical model for the transmission dynamics of hepatitis B virus (HBV) infection incorporating vaccination and treatment as control parameters is presented. The basic reproduction number, , as a threshold parameter, was constructed, in terms of the given model parameters, by the next generation method. was numerically assessed for its sensitivity to vaccination and treatment parameters. A unique disease-free equilibrium state was determined, indicating possibility of control of HBV disease. The model was solved numerically using Runge-Kutta method of order four to evaluate the effects of vaccination and treatment parameters on the prevalence of the disease. The numerical results of the sensitivity analysis show that increasing either vaccination or treatment rate has the potential of reducing below unity. The results of the numerical simulations of the model show that effective vaccination, treatment or a combination of both of them as a control strategy can eradicate HBV disease, with the combination being far better than either of them. Finally, these findings strongly suggest that high coverage of vaccination and treatment are crucial to the success of HBV disease control.

Forecasting Precipitation Using SARIMA Model: A Case Study of Mt. Kenya Region

Abstract: Precipitation estimates are an important component of water resources applications, example, in designing drainage system and irrigation. The amount of rainfall in Kenya fluctuates from year to year causing it to be very hard to predict it through empirical observations of the atmosphere alone. Our objective was to determine the forecasted values of precipitation in Mt. Kenya region and also to determine the accuracy of the SARIMA model in forecasting precipitation in the same region. This research considers a univariate time series model to forecast precipitation in Mt. Kenya region. We fitted the SARIMA model to our data and we picked the model which exhibited the least AIC and BIC values. Finally, we forecasted our data after following the three Box-Jenkins methodologies, that is, model identification, estimation of parameters and diagnostic check. Having three tentative models, the best model had two highly significant variables, a constant and with p-values< 0.01 respectively . This model passed residual normality test and the forecasting evaluation statistics shows ME= -0.0053687, MSE=0.96794, RMSE=0.98384 and MAE= 0.75197. Indeed, SARIMA model is a good model for forecasting precipitation in Mt. Kenya region Keywords: SARIMA, Precipitation, Forecast, Mt. Kenya, AIC and BIC

Empirical Modelling and Model Selection for Forecasting Monthly Inflation of Ghana

Abstract: Inflation is the persistent increase in the level of consumer prices or a persistent decline in the purchasing power of money. Inflation is of global concerns because it can distort economic patterns and can result in the redistribution of wealth when not anticipated, thus there is a need to know the pattern of inflation in the country. In this study, we employed an empirical modeling and model selection for monthly inflation in Ghana from January 2009 to December 2013 using the Box-Jenkins approach. The results showed that ARIMA (1, 2, 1) model was appropriate for modelling the inflation rates with a maximum log likelihood value of -64.21, and least AIC value of 134,43, AICc value of 134.87 and BIC value of 140. 61. An ARCH-LM test and Ljung-Box test on the residuals of the models revealed that the residuals are free from heteroscedasticity and serial correlation respectively. Ghana is likely to experience a persistence increase in inflation rate with double digit hence the government should reconsider his monetary policies. Keywords: Inflation, Box-Jenkins, Empirical, Ghana.

A New (Proposed) Formula for Interpolation and Comparison with Existing Formula of Interpolation

Abstract: The word “interpolation” originates from the Latin verb interpolare, a contraction of “inter,” meaning “between,” and “polare,” meaning “to polish.” That is to say, to smooth in between given pieces of information. A number of different methods have been developed to construct useful interpolation formulas for evenly and unevenly spaced points. The aim of this paper is to develop a central difference interpolation formula which is derived from Gauss’s Backward Formula and another formula in which we retreat the subscripts in Gauss’s Forward Formula by one unit and replacing by . Also, we make the comparisons of the developed interpolation formula with the existing interpolation formulas based on differences. Results show that the new formula is very efficient and posses good accuracy for evaluating functional values between given data. Keywords: Interpolation, Central Difference, Gauss’s Formula.

A Novel Numerical Approach for Odd Higher Order Boundary Value Problems

Abstract: In this paper, we investigate numerical solutions of odd higher order differential equations, particularly the fifth, seventh and ninth order linear and nonlinear boundary value problems (BVPs) with two point boundary conditions. We exploit Galerkin weighted residual method with Legendre polynomials as basis functions. Special care has been taken to satisfy the corresponding homogeneous form of boundary conditions where the essential types of boundary conditions are given. The method is formulated as a rigorous matrix form. Several numerical examples, of both linear and nonlinear BVPs available in the literature, are presented to illustrate the reliability and efficiency of the proposed method. The present method is quite efficient and yields better results when compared with the existing methods. Keywords: Galerkin method, fifth, seventh and ninth order linear and nonlinear BVPs, Legendre Polynomials.

Rice Production Forecasting in Bangladesh: An Application Of Box-Jenkins ARIMA Model

Abstract: The study was undertaken to fit the best Auto-Regressive Integrated Moving Average (ARIMA) model that could be used to forecast the rice productions of Bangladesh such as in Aus, Boro, Aman season covering the whole country. This data for the present study is available in the Bangladesh Agricultural Ministry’s websites www.moa.gov.bd. The best selected ARIMA model for Aus productions is ARIMA (2,1,2), for Aman it is ARIMA (2,1,2) and, for Boro it is ARIMA (1,1,3). In this study, it was tried to make a comparison between the original series and forecasted series which also shows the same manner indicating fitted model are statistically well behaved to forecast rice productions in Bangladesh. It is found from the analysis that ARIMA model gives good forecasting for short term analysis. KEYWORDS: Rice production, ARIMA, Forecasting, Bangladesh.

Immunization Coverage of Pregnant Women with Tetanus Toxoid Vaccine in Dormaa East District-Brong Adaro Region, Ghana

Abstract: This paper examines the immunization coverage of Tetanus toxoid vaccine in the Dormaa East District and then assesses the reasons for the low coverage in the district as to whether it is as a result of the attitude of health staff, knowledge of beneficiaries on its importance or the accessibility of the health facilities. Our findings suggest that, most beneficiaries fail to get immunized due to the reasons that they are not treated well by health workers on their visit to the immunization Centres. The beneficiaries are also unaware of when to be immunized and do not see the relevance of being immunized. Getting access to the vaccination centre is another cause for dropping-out in the course of immunization. It is recommended to the stakeholders to design and implement appropriate and relevant immunization programmes that will serve to improve EPI service utilization in the Dormaa East District Health Administration by embarking on routine educational campaign at both antenatal and postnatal sessions and child welfare clinics. There is the need to stress on the total number of times mothers need to visit the clinic to complete the immunization and the importance of being immunized. Also mother’s immunization for tetanus toxoid vaccine should be given equal attention by all health workers just like the immunization for their children during antenatal care attendance. The health staffs should also try making the beneficiaries feel good when they appear for their service. Enough immunization service centers should be made available close to the various communities to enable the people get quick access to it. Keywords : maternal and neonatal tetanus, Tetanus Toxoid immunization and regression analysis.

Estimation of Irrigation Water Demand in Rice Production Tanzania

Abstract: The agriculture sector is one of the major users of water resource for irrigation activities. In Tanzania irrigation water demand for rice is still increasing due to the area being irrigated continues to expand while the amount of water for irrigation is decreasing. The purpose of this paper was to develop the demand function for estimation of irrigation water in rice production in Tanzania. The secondary data were collected from various sources such as the Ministry of Agriculture, Food Security and Cooperatives at Statistics Unit, and relevant basin authorities and zonal irrigation units. A demand function was estimated after carrying out the relevant statistical tests. The Breush and Pagan Lagrangian Multiplier Test were used to select whether to use the Pool or Panel Data approaches. The Panel model was verified to be more suitable than the Pool model. The fixed effect and random effect were compared in the Hausman’s specification test. The price elasticity of irrigation water demand and other elasticity were also estimated using Ordinary Least Squares facilitated by STATA 11. A panel data of 16 regions of Tanzania in the period of 2007 - 2012 were used. The estimated average water demand found to be 8000m 3 /ha whereas water productivity in rice cultivation found to be 0.3kg/m 3 . Keywords: Water demand function, Water productivity, Panel data, Rice, Irrigation water

Modeling the Effect of Screening and Treatment on the Transmission of Tuberculosis Infections

Abstract: Tuberculosis (TB) is a chronic airborne disease caused mainly by Mycobacterium tuberculosis and has caused many deaths globally and Tanzania in particular due to failure or delayed intervention. In this paper, a deterministic mathematical model for transmission dynamics of TB with vaccination and screening the population for the purpose of identifying those for immediate treatment is formulated. The effective reproduction number is computed in order to measure the relative impact for individual or combined intervention for effective disease control. Numerical simulations of the basic reproduction number shows that, the combination of vaccination, screening and treatment is the most effective intervention for minimizing the transmission of TB in a population. Key words : Tuberculosis, Modeling, Screening, Treatment.

Ranking Function Methods For Solving Fuzzy Linear Programming Problems

Abstract: In this paper, we concentrate on linear programming problems in which the coefficients of objective function are fuzzy numbers, the right-hand side are fuzzy numbers too, and both the coefficients of objective function as well as right-hand side are fuzzy numbers. Then solving these fuzzy linear programming problems by using many linear ranking functions. After that develop six numerical examples to illustrates the steps of solutions for all these type of linear programming problems which studying in this paper. Keywords: Fuzzy set theory, fuzzy linear programming, linear ranking function, trapezoidal membership.

Application of paired student t-test on impact of Anti-retroviral therapy on CD4 cell count among HIV Seroconverters in serodiscordant heterosexual relationships: A case study of Nyanza region, Kenya.

Abstract: Human immunodeficiency virus (HIV) infection leads to rise in HIV-RNA resulting in CD4 T-cell decline leading to AIDS-related illness. Knowing the effect of Antiretroviral Therapy (ART) on CD4 cell count is vital in assessing the progression of the disease and treatment planning for treatment. This study sought to apply paired t-test distribution to assess the effect of CD4 cell count just before and after initiation of ART among HIV infected individuals. The target populations were HIV sero-converters enrolled in a prospective randomized placebo controlled trial in Nyanza region, Kenya. CD4 cell count was measured at the time of sero-conversion and subsequently after very six months of follow up. Participants were referred for initiation of ART at patient support centre once the criteria for initiation was met and report back the ART regime they were put on and the date they were started on . We applied paired t-test to assess the change in CD4 cell count after initiating ART. Use of ART within a median time of 9 months resulted rise in CD4 cell count by 241 cells per ul, 95% CI (60-422) which confirms the effect of ART in protecting depletion of CD4 cell count. Keywords: Sero-converters, Progression, ART, HIV, CD4 cells, t-test.

Modeling the Impact of Immunization on the Epidemiology of Varicella Zoster Virus.

Abstract: Chickenpox (also called varicella) is a disease caused by virus known as varicella-zoster virus (VZV) also known as human herpes virus 3 In this paper, a deterministic mathematical model for transmission dynamics of VZV with vaccination is formulated The effective reproduction number is computed in order to measure the relative impact for individual or combined intervention for effective disease control Numerical simulations of the basic reproduction number of the model shows that, the combination of vaccination and treatment is the most effective way to combat the epidemiology of VZV in the community Keywords: Modeling, Treatment, Vaccination, Epidemiology

An application of queueing theory to ATM service optimization: a case Study

Abstract: Unmanaged queues are detrimental to the gainful operation of service systems and results in a lot of other managerial problems. This paper applies queuing theory to determine optimal service level for a case ATM base on a customer-defined criterion of wait time not exceeding eight (8) minutes. In pursuance of this, the prevailing operation characteristics of the case ATM as a queuing system where defined. Direct non-participatory observation and questionnaire were engaged to record time measurements and primary data. Measurements were taken on arrival times and service times of customers who arrived at the terminal within the hours of 8:00 am to 4:00 pm. The Chi-squared Goodness of Fit test was performed on collected data. This established the interarrival times at the case ATM as exponentially distributed. The M/M/s queuing model therefore best illustrates the ATM queuing system of the case bank. A queuing theory based decision support system was developed as a result and applied to analyse and suggest improvement in waiting time. Two ATMs at a service rate of 0.60 customers per minute is found to be optimal for the case bank albeit waiting time are found to be relatively higher during the hours of 11:00am to 1:00pm and month endings. The research thus reveals that although queuing theory is applicable in finding optimal service levels, waiting time might still be lengthy because of external factors. Service unavailability was observed to be a contributory factor to queue formation at the case ATM. A routine maintenance regime should be actively implemented in curtailing such problems. For short term queue management however, backup-staffs could be engaged during peak periods to handle any additional demand instead of the alternative of installing the rather capital intensive ATM which might be of less utility for most business hours. Queue management should also be made an active part of the bank’s overall strategic queue management processes. Keywords: Queuing Theory, Waiting Time, Service Rate, Arrival Rate, ATM, Optimal Service Level

Trends in Transitive p-Groups and Their Defining Relations

Abstract: In this paper unless otherwise stated the letter represents a fixed prime number. The concept of p- groups is fundamental in the theory of groups. Sylow theorems will be assumed known in this paper. In classifying finite groups we know in the Abelian case that the number of groups of order n is influenced largely by the character of the prime factorization of n, and not by the size of n alone. Any finite group G contains the so called Sylow p-subgroups which are p-groups and are closely linked to the structure of G. Recent developments in theory of finite simple groups have brought insights on p-groups and have suggested investigations in diverse areas. In this paper, however, we shall present some of the most basic results on transitive p-groups and their defining relations. Keywords: transitive -groups, isomorphism, classification

Application of Markov Chain Model in Studying progression Of Secondary School Students by Sex During The Free Secondary Education: A Case Study of Kisii Central District

Abstract: Enrollment forecasting is an essential element in budgeting, resource allocation, and the overall planning for the growth of education sector. This paper demonstrates the use of Markov chain techniques in studying progression of secondary school students from the time of entry/enrollment in form one to graduation after the expected four years in Kenya’s secondary school level of education. The target population included all the secondary school students in Kisii Central District. The model was used to determine the district’s secondary school completion/dropout rate, retention rate and the expected duration of schooling by sex. It was established that completion rates for male students was higher than that of female students and dropout rates for female students was higher than that of male students. In the long run, it was established that the completion and dropout rates were the absorbing rates. Female students had lower expectation of schooling compared to male students in Kisii Central District. The model is only appropriate in making short period projections. Keywords: Absorbing States, Absorbing Markov Chain, Transition Rates, Dropout Rates, Completion Rates, Fundamental Matrix

Bayes Estimators for the Shape Parameter of Pareto Type I Distribution under Generalized Square Error Loss Function

Abstract: In this paper, we obtained Basyian estimators of the shape parameter of the Pareto type I distribution using Bayian method under Generalized square error loss function and Quadratic loss function. In order to get better understanding of our Bayesian analysis we consider non-informative prior for the shape parameter Using Jeffery prior Information as well as informative prior density represented by Exponential distribution. These Bayes estimators of the shape parameter of the Pareto type I distribution are compared with some classical estimators such as, the Maximum likelihood estimator (MLE), the Uniformly minimum variance unbiased estimator (UMVUE), and the Minimum mean squared error (MinMSE) estimator according to Monte-Carlo simulation study. The performance of these estimators is compared by employing the mean square errors (MSE’s). Key words: Pareto distribution; Maximum likelihood estimator; Uniformly minimum variance unbiased estimator; Minimum mean squared error; Bayes estimator; Generalized square error loss function; Quadratic loss function; Jeffery prior; Exponential prior.

Linear regression model with generalized new symmetric error distribution

Abstract: Linear models play a dominant role in analyzing several data sets arising at places like agricultural experiments, space experiments, biological experiments, financial modeling and a wide range other practical problems. One of the major strings in the development of the regression model is the assumption of the error. It is often assumed that the random error of the linear regression model is normally distributed. In numerous situations, however, it is nearly impossible to find a data set that satisfies the normality assumption due to various reasons, such as multivariate skewed and/or heavy-tailed distributions. This problem has been addressed by specifying a different parametric distribution family for the error terms. In this paper, a linear regression model with generalized new symmetric errors is developed and analyzed. The Maximum Likelihood (ML) estimators of the model parameters are derived and their properties with respect to the generalized new symmetric distributed errors are discussed. Simulations were carried out to study the performance of the proposed model with that of Gaussian errors and found that the proposed model perform well when the variables are platykurtic. Some applications of the developed model are also pointed. Key Words : Generalized new symmetric distribution, Regression model, Simulation