NUMERICAL METHODS FOR ESTIMATION AND INFERENCE IN BAYESIAN VAR-MODELS

In Bayesian analysis of vector autoregressive models, and especially in forecasting applications, the Minnesota prior of Litterman is frequently used. In many cases other prior distributions provide better forecasts and are preferable from a theoretical standpoint. Several of these priors require numerical methods in order to evaluate the posterior distribution. Different ways of implementing Monte Carlo integration are considered. It is found that Gibbs sampling performs as well as, or better, then importance sampling and that the Gibbs sampling algorithms are less adversely affected by model size. We also report on the forecasting performance of the different prior distributions. © 1997 by John Wiley & Sons, Ltd.     

Clothing for the elderly at home and in nursing homes

Age-related changes and clothing problems of elderly people at home and in nursing homes have been systematically studied in both an objective and a subjective way with medical literature studies, interviews and user studies. There are certain demands which the clothing design must meet in order to fulfil the requirements specified by the functional ability of the ageing individual. The consequences of the age-related changes on the construction of clothing are analysed and some clothing examples described.