@article{Radhalakshmi_William_2021, title={A Class of Univariate Non-Mesokurtic Distributions Using a Continuous Uniform Symmetrizer and Chi Generator}, volume={81}, url={https://rivista-statistica.unibo.it/article/view/12336}, DOI={10.6092/issn.1973-2201/12336}, abstractNote={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 ’univariate non-mesokurtic normal’ 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.}, number={2}, journal={Statistica}, author={Radhalakshmi, Kamala Naganathan and William, Martin Luther}, year={2021}, month={Jan.}, pages={217–227} }