TY - JOUR
AU - Radhalakshmi, Kamala Naganathan
AU - William, Martin Luther
PY - 2021/01/01
Y2 - 2023/02/01
TI - A Class of Univariate Non-Mesokurtic Distributions Using a Continuous Uniform Symmetrizer and Chi Generator
JF - Statistica
JA - Stat
VL - 81
IS - 2
SE - Articles
DO - 10.6092/issn.1973-2201/12336
UR - https://rivista-statistica.unibo.it/article/view/12336
SP - 217-227
AB - In a good number of real life situations, the observations on a random variable of interest tend to concentrate either too closely or too thinly around a central point but symmetrically like the normal distribution. The symmetric structure of the density function appears like that of a normal distribution but the concentration of the observations can be either thicker or thinner around the mean. This paper attempts to generate a family of densities that are symmetric like normal butwith different kurtosis. Drawing inspiration from a recent work on multivariate leptokurtic normal distribution, this paper seeks to consider the univariate case and adopt a different approach to generate a family to be called â€™univariate non-mesokurtic normalâ€™ family.The symmetricity of the densities is brought out by a uniform random variable while the kurtosis variation is brought about by a chi generator. Some of the properties of the resulting class of distributions and the pameter estimation are discussed.
ER -