Analyzing Near-Normal Data Using a New Density Function within Azzalini’s Class of Skew Distributions
نویسندگان
چکیده
A family of distributions, which was first introduced by O’Hagan and Leonard [9] for Bayesian analysis of normal means and was later investigated in detail by Azzalini [3, 4], is modified leading to a new class of asymmetric distributions. A new score test is derived for detecting non-normality within the new class of asymmetric distributions. The maximum likelihood estimates are derived for location, scale, shape, and skewness parameters. Then, the new score test is applied on an example of a real data set within the new class of asymmetric distributions to detect non-normality. Maximum likelihood estimators are used to fit the data with a skew distribution and compared to studies in which researchers used the normal distribution.
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