Journal of Data Mining in Genomics & Proteomics

The effects of square root transformation on a gamma distributed error component of a Multiplicative Error Model (MEM)

2^nd International Conference on Big Data Analysis and Data Mining

November 30-December 01, 2015 San Antonio, USA

Dike O A1 and Ohakwe J2

1Akanu Ibiam Federal Polytechnic, Nigeria 2Federa University, Nigeria

Posters-Accepted Abstracts: J Data Mining In Genomics & Proteomics

Abstract:

In this paper, we studied the effect of square root transformation on a Gamma distributed error component of a Multiplicative Error Model (MEM) with mean 1.0 with a view to establishing the condition for the successful transformation. The probability density function (pdf), first and second moments of the square root transformed error component (et*) were established. From the results of the study, it was found that the square root transformed error component was normal with unit mean and variance, approximately ¼ times that of the original error (et) before transformation except when the shape parameter is equal to one. However, Anderson Darling�??s test for normality on the simulated error terms confirmed normality for et* at (P<0.05). These showed that the square root transformation normalizes a non-normal Gamma distributed error component. Finally, numerical illustrations were used to back up the results established. Thus, a successful square root transformation is achieved when 1/4�?2<1.0 which implies that �?2�?�¼.

Biography :

Dike O A has completed his MSc in Statistics from Abia State University, Uturu, and Doctoral in Statistics at Abia State University, Uturu. He is the Head of Department of Mathematics/Statistics in Akanu Ibiam Federal Polytechnic, Unwana, Nigeria. He has published more than 10 papers in reputed journals and is currently serving as a Reviewer in Central Bank of Nigeria (CBN) Journal of Applied Statistics and a member Editorial Board of School of Science Journal.

Email: dikeawa@gmail.com