원문정보
초록
영어
If normality of an observed data is not a viable assumption, we can carry out normal-theory analyses by suitable transforming data. Power transformation by Box and Cox, one of the transformation methods, is derived the power which maximized the likelihood function. But it doesn't induces the closed form in mathematical analysis. In this paper, we compose some R the syntax of which is easier than other statistical packages for deriving the power with using numerical methods. Also, by using R, we show the transformed data approximately distributed the normal through Q-Q plot in univariate and bivariate cases with some examples. Finally, we present the value of a goodness-of-fit statistic(AD) and its p-value for normal distribution. In the similar procedure, this method can be extended to more than bivariate case.
목차
1. Introduction
2. R-program and It’s Application for Box-Cox Transformation of Univariate Data
2.1. R–program for Univariate Box-Cox Transformation
2.2. An Example Using R-Program for Univariate Box-Cox Power Transformation
3. R-Program and Its Appication for Box-Cox Transformation of Bivariate Data
3.1. R-program for Box-Cox Transformation of Bivariate Data
3.2. An Example Using R-program for Bivariate Box-Cox Power Transformation
4. Conclusions and suggestions
Acknowledgements
References