Semiparametric Gaussian Variance-Mean Mixtures for Heavy-Tailed and Skewed Data

Table 1

Posterior quantile estimation to show the model fitting. Posterior quantile C.I.s are obtained by simulating 200 reconstructed datasets based (each consisting of 5000 data points) on posterior samples of unknown quantities, each dataset giving one set of quantile point estimates. Observed quantiles are obtained from the 1000 observed simulated data.

Quantiles	Observed	Posterior	Posterior 95%
	quantile	mean	C.I.
2.5%	−1.474	−1.492	[−1.535, −1.450]
5%	−1.328	−1.322	[−1.363, −1.284]
25%	−0.738	−0.711	[−0.742, −0.676]
50%	−0.175	−0.162	[−0.190, −0.124]
75%	0.555	0.534	[0.492, 0.584]
95%	1.783	1.871	[1.776, 1.985]
97.5%	2.394	2.414	[2.283, 2.566]