{"id":297,"date":"2017-04-24T12:27:06","date_gmt":"2017-04-24T12:27:06","guid":{"rendered":"http:\/\/jsr.isrt.ac.bd\/?post_type=article&p=297"},"modified":"2017-04-24T12:27:14","modified_gmt":"2017-04-24T12:27:14","slug":"mathematical-methods-constructing-generalizations-skew-normal-distributions","status":"publish","type":"article","link":"http:\/\/jsr.isrt.ac.bd\/article\/mathematical-methods-constructing-generalizations-skew-normal-distributions\/","title":{"rendered":"Mathematical Methods of constructing Generalizations Skew Normal Distributions"},"content":{"rendered":"
In this paper, two different mathematical methods are used to derive skew distributions.
\nThe results generalize Azzalini (1985) and Fern\u00b4andez and Steel (1998) skew distributions
\ngenerating new results in general, and skew normal distribution in particular. Some mathematical
\nproperties, such as n-th moments, distribution function, moments generating function,
\nare also given for the generalizations. Some known and new special cases are also
\nmentioned. Some graphs for skew distributions are included. Results are applied to two
\npractical problems. Shannon and Renyi entropies as well as Fisher information are also
\nobtained.<\/p>\n
<\/p>\n