A Bayesian Markov Chain Monte Carlo methodology is developed for estimating the stochastic conditional duration model. The conditional mean of durations between trades is modelled as a latent stochastic process, with the conditional distribution of durations having positive support. Regressors are included in the latent process model in order to allow for additional variables to impact on durat...

In this paper, we propose a new method to estimate the multivariate conditional density, f(mjx), a density over the output space m conditioned on any given input x. In particular, we are interested in cases where the number of available training data points is relatively sparse within x space. We start from a priori considerations and establish certain desirable characteristics in kernel functi...

Campbelll1] derived and deened a quantity called the coeecient rate of a random process that involves the process spectral entropy. Two new derivations of Campbell's coeecient rate are given here. One derivation solidiies the interpretation of this quantity as a coeecient rate, while the second derivation implies a new approach for source compression. We investigate this new approach for transf...

In mining projects, all uncertainties associated with a project must be considered to determine the feasibility study. Grade uncertainty is one of the major components of technical uncertainty that affects the variability of the project. Geostatistical simulation, as a reliable approach, is the most widely used method to quantify risk analysis to overcome the drawbacks of the estimation methods...

We propose the use of Heaviside transform with respect to the quark mass to investigate dynamical aspects of QCD. We show that at large momentum transfer the transformed propagator of massive quarks behaves softly and thus the dominant effect of explicit chiral symmetry breaking disappears through Heaviside transform. This suggests that the massless approximation would be more convenient to do ...