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 Darlingâ??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 1/4Ï?2<1.0 which implies that Ï?2â?¤Â¼.

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