ABSTRACT
We will begin with providing the requisite information for the univariate g-and-h and GLD families of transformations. Numerical examples are provided to demonstrate the two transformations in terms of computing cumulants, measures of central tendency, quantiles, distribution fitting, and in terms of graphing pdfs and cdfs. It is also demonstrated how the g-and-h, GLD, and power method transformations can be used to simulate or model combined data sets when only the mean, variance, skew, and kurtosis associated with the underlying individual data sets are available; that is, the raw data points are not available or accessible.
