the  main  assumptions  in  liner  mixed  model  are normality  and  independency  of  random  effect component.   unfortunately,   these   two  assumptions   might   be  unrealistic   in  some   situations. therefore, in this paper, we will discuss about the analysis of bayesian analysis of non-normal and non-independent mixed model using skew-normal/independent distributions, and finally, thi...

This paper is concerned with the multivariate extended skew-normal [MESN] and skew-Student [MEST] distributions, that is, distributions in which location parameters of underlying truncated are not zero. The extra parameter leads to greater variability moments critical values, thus providing flexibility for empirical work. It reported this various theoretical properties notably limiting forms as...

The skew t-distribution is a flexible model able to deal with data whose distribution show deviations from normality. It includes both the skew normal and the normal distributions as special cases. Inference for the skew t-model becomes problematic in these cases because the expected information matrix is singular and the parameter corresponding to the degrees of freedom takes a value at the bo...

The amplitude distribution of miniature postsynaptic currents (minis) in many central neurons has a large variance and positive skew, but the sources of this variance and skew are unresolved. Recently it has been proposed that spontaneous Ca2+ influx into a presynaptic bouton with multiple release sites could cause spontaneous multiquantal minis by synchronizing release at all sites in the bout...

In this paper, we derive recurrence relations for cumulative distribution functions (cdf’s) of bivariate t and extended skew-t distributions. These recurrence relations are over ν (the degrees of freedom), and starting from the known results for ν = 1 and ν = 2, they will allow for the recursive evaluation of the distribution function for any other positive integral value of ν. Then, we conside...