14 results for “S. J. Kayode”

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Research ArticleOpen accessIn the author namesA Multiderivative Collocation Method for 5th Order Ordinary Differential EquationsS. J. Kayode, D. O. AwoyemiProblem statement: The conventional methods of solving higher order differential equations have been by reducing them to systems of first order equations. This approach is cumbersome and increases computational time. Approach: To address this problem, a numerical algorithm for direct solution of 5th order initial value problems in ordinary differential equations (odes), using power series as basis function, is proposed … …Journal of Mathematics and Statistics, Vol. 6, Issue 1 · 31 Mar 2010 · 8,928 accessesView PDF Cite

Research ArticleOpen accessIn the author namesAn Order Six Zero-Stable Method for Direct Solution of Fourth Order Ordinary Differential EquationsKayode Sunday JacobA zero-stable numerical method for direct solution of fourth order differential equations reduces the computational burden and computer time wastage involved in the method of reducing such equations to a system of first order equations. The method adopted is the collocation of the differential system and the interpolation of the approximate solution to the problem using the power series as … …American Journal of Applied Sciences, Vol. 5, Issue 11 · 30 Nov 2008 · 7,170 accessesView PDF Cite

Research ArticleOpen accessIn the author namesEffect of Multicollinearity on Power Rates of the Ordinary Least Squares EstimatorsO.O. Alabi, Kayode Ayinde, T.O. OlatayoInferences on the parameter estimates of Ordinary Least Square (OLS) estimator in regression model when regressors exhibit multicollinearity is a problem in that large standard errors of the regression coefficients which cause low t-statistic value often result into the acceptance of the null hypothesis. This paper, therefore, makes efforts to investigate the effect of multicollinearity on the power rates of … …Journal of Mathematics and Statistics, Vol. 4, Issue 2 · 30 Jun 2008 · 7,880 accessesView PDF Cite

Research ArticleOpen accessIn the author namesA Comparative Study of the Performances of the OLS and some GLS Estimators when Stochastic Regressors are both Collinear and Correlated with Error TermsKayode AyindeThe Classical Linear Regression Model assumes that regressors are non – stochastic, independent and uncorrelated with the error terms. These assumptions are not always tenable especially where regressors are not often assumed fixed in repeated sampling. In this paper, with stochastic regressors, the performances of the Ordinary Least Square (OLS) and some Generalized Least Square (GLS) estimators are investigated and … …Journal of Mathematics and Statistics, Vol. 3, Issue 4 · 31 Dec 2007 · 7,343 accessesView PDF Cite