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, skewness, and tail-heaviness measures, which are estimates of specific parameters of the underlying population distribution … of asymmetric distributions. In this article, we briefly compare, for each type of parameter (location, scale, skewness …
Persistent link: https://www.econbiz.de/10011265691
assumption, it is important to simulate data from a nonnormal distribution with varying degrees of skewness and kurtosis … values for the skewness and kurtosis. Vale and Maurelli (1983, Psychometrika 48: 465–471) extended Fleishman’s method to …
Persistent link: https://www.econbiz.de/10011265703
Graphing univariate distributions is central to both statistical graphics, in general, and StataÕs graphics, in particular. Now that Stata 8 is out, a review of official and user-written commands is timely. The emphasis here is on going beyond what is obviously and readily available, with...
Persistent link: https://www.econbiz.de/10005178354
Nonnormal data arise often in practice, prompting the development of flexible distributions for modeling such situations. In this article, we describe two multivariate distributions, the skew-normal and the skew-t, which can be used to model skewed and heavy-tailed continuous data. We then...
Persistent link: https://www.econbiz.de/10008784393
Sample skewness and kurtosis are limited by functions of sample size. The limits, or approximations to them, have …
Persistent link: https://www.econbiz.de/10008677203