We represent random vectors Z that take values in n-{0} as Z=RY, where R is a positive random variable and Y takes values in an (n-1)-dimensional space . By fixing the distribution of either R or Y, while imposing independence between them, different classes of distributions on n can be...

This paper provides a Bayesian analysis of Autoregressive Fractionally Integrated Moving Average (ARFIMA) models. We discuss in detail inference on impulse responses, and show how Bayesian methods can be used to (i) test ARFIMA models against ARIMA alternatives, and (ii) take model uncertainty...

This paper develops Bayesian approaches to deal with linear elliptical regression models that differ in the covariance structure. A pretest method based on posterior model probabilities is compared with a pooling approach, and the data density is defined as a mixture of elliptical densities with...

We consider Bayesian inference via Markov chain Monte Carlo for a variety of fractal Gaussian processes on the real line. These models have unknown parameters in the covariance matrix, requiring inversion of a new covariance matrix at each Markov chain Monte Carlo iteration. The processes have...

The reference prior algorithm [Berger and Bernardo, 1992, Bayesian Statistics 4, Oxford University Press, Oxford, pp. 35-60] is applied to multivariate location-scale models with any regular sampling density, where we establish the irrelevance of the usual assumption of Normal sampling if our...

This paper explores options for supporting the Government of Suriname's Green Vision and Strategy, with its corresponding policies and activities, as input for the Bank's 2011-2014 Country Strategy. It briefly describes Suriname's salient environmental and social characteristics and its major...