Big Data Analysis and Data Mining

Biography

Biography: Dike O.A.

Abstract

In this paper, we studied the effect of square root transformation on a Gamma distributed error component of a multiplicative error model with mean 1.0with 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, approximately1/4times 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.