We introduce a multivariate stochastic volatility model that imposes no restrictions on the structure of matrix and treats all its elements as functions latent processes. Inference is achieved via carefully designed feasible scalable MCMC has quadratic, rather than cubic, computational complexity for evaluating normal densities required. illustrate how our can be applied macroeconomic applicati...

the most commonly used utility functional forms are reviewed and their properties compared. then, using data collected from west azarbaijan province, utility functions are estimated and absolute risk aversion coefficients measured. exponential and expopower utility functions classified all farmers as risk averse, but quadratic and cubic utility functions classified 75% and 65% of farmers as...

Abstract Understanding causal relationships is one of the most important goals modern science. So far, inference literature has focused almost exclusively on outcomes coming from Euclidean space Rp. However, it increasingly common that complex datasets are best summarized as data points in nonlinear spaces. In this paper, we present a novel framework effects for Wasserstein cumulative distribut...

We approximate a fuzzy almost quadratic function by a quadratic function in a fuzzy sense. More precisely, we establish a fuzzy Hyers–Ulam–Rassias stability of the quadratic functional equation f(x + y) + f(x − y) = 2f(x) + 2f(y). Our result can be regarded as a generalization of the stability phenomenon in the framework of normed spaces. We also prove a generalized version of fuzzy stability o...

Higher order energy functions have the ability to encode high level structural dependencies between pixels, which have been shown to be extremely powerful for image labeling problems. Their use, however, is severely hampered in practice by the intractable complexity of representing and minimizing such functions. We observed that higher order functions encountered in computer vision are very oft...