Summarizing Shape Numerically: The g‐and‐h Distributions

235 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

On Families of Distributions with Shape Parameters (2015, unknown): “A popular alternative two-parameter transformation is that associated with the g -and- h distributions (Hoaglin, 1985): Here, I use the eponymous parametrization that hopefully causes no confusion with my use of g as base density; g -and- h distributions themselves take my g = φ but other g could…”
Sensitivity of normality tests to non-normal data (2011, methodology): “The other two distributions were obtained from the g-distribution and h-distribution from Hoaglin (1985).”
Sisvar: a Guide for its Bootstrap procedures in multiple comparisons (2014, methodology): “Initially, samples were simulated from k populations, considering the probabilistic model called g-h (Hoaglin, 1985).”
Robust regression: an inferential method for determining which independent variables are most important (2018, unknown): “generated from g-and-hdistributions [9], which arise as follows.”
Comparing two independent groups via the lower and upper quantiles (2014, methodology): “More precisely, four g-and-h distributions were used [13] that contain the standard normal distribution as a special case.”