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Felix O. Mettle

Publications (4)

A Proposed Method for Numerical Integration

Felix O. Mettle, Enoch N. B. Quaye, Louis Asiedu & Kwasi A. Darkwah · Journal of Advances in Mathematics and Computer Science · 2016

The main objective of this paper is to propose a numerical integration method that provides improved estimates as compared to the Newton-Cotes methods of integration. The method is an extension of trapezoidal rule where after segmentation, the top part of each segment was further...

Open access Research Article 10.9734/BJMCS/2016/23048

Comparison of Least Squares Method and Bayesian with Multivariate Normal Prior in Estimating Multiple Regression Parameters

Felix O. Mettle, Louis Asiedu, Enoch N. B. Quaye & Abeku A. Asare-Kumi · Journal of Advances in Mathematics and Computer Science · 2016

Based on an assumption of multivariate normal priors for parameters of multivariate regression model, this study outlines an algorithm for application of traditional Bayesian method to estimate regression parameters. From a given set of data, a Jackknife sample of least squares r...

Open access Research Article 10.9734/BJMCS/2016/23145

A Study of the Estimation of the Gini Coefficient of Income Using Lorenz Curve

Kwasi A. Darkwah, Ezekiel N. N. Nortey, Felix O. Mettle & Isaac Baidoo · Journal of Advances in Mathematics and Computer Science · 2016

Aims: This paper compares the Boole and Weddle numerical integration methods to estimate the Lorenz curve and Gini Coefficient of income in Ghana. Study Design:  Research Paper. Place and Duration of Study: Ghana, Secondary data for 2013 Ghana Living Standard Survey. Methodology:...

Open access Research Article 10.9734/BJMCS/2016/24494

Statistical Assessment of PCA/SVD and FFT-PCA/SVD on Variable Facial Expressions

Louis Asiedu, Atinuke O. Adebanji, Francis T. Oduro & Felix O. Mettle · Journal of Advances in Mathematics and Computer Science · 2015

Face recognition is a dedicated process in the human brain. Automatic face recognition is rewarding since an efficient and resilient recognition system is useful in many application areas. Recent face recognition algorithms are still faced with the challenge of recognizing face i...

Open access Research Article 10.9734/BJMCS/2016/22141