Table 1.

Monte Carlo approximations of mean absolute errors for point estimates of pr(W_n+1 > w | x_n+1) for some values of x_n+1 and w: a comparison between mixtures of multivariate Polya trees and dependent mixtures of log-normal densities specified with kernel stick breaking processes (Dunson, 2008). Covariate values are 0.25, 0.50 and 0.75. For each value of x_n+1 we consider w equal to the 25th, 50th and 75th percentile of the corresponding truncated normal distribution.

	Mean absolute errors
	xn+1	w = 25th percentile	w = 50th percentile	w = 75th percentile
mmpt	0.25	0.044	0.049	0.041
	0.50	0.042	0.046	0.040
	0.75	0.047	0.049	0.042
ksbp	0.25	0.042	0.050	0.045
	0.50	0.043	0.051	0.042
	0.75	0.045	0.047	0.046

mmpt, mixtures of multivariate Polya trees; ksbp, kernel stick breaking process.