Several Bayesian and classical models are used to forecast house prices in 20 states in
the United States. There are two approaches: extracting common factors (principle
components) in a factor-augmented vector autoregressive or factor-augmented Bayesian
vector autoregressive models or Bayesian shrinkage in a large-scale Bayesian vector
autoregressive models. The study compares the forecast performance of the 1976:Q1 to
1994:Q4 in-sample period to the out-of-sample horizon 1995:Q1 to 2009:Q1 period. The
findings provide mixed evidence on the role of macroeconomic fundamentals in
improving the forecasting performance of time-series models. For 13 states, models that
include the information of macroeconomic fundamentals improve the forecasting
performance, while for seven states they do not.
Olivier, Laurentz Eugene; Craig, Ian K.(Elsevier, 2013-02)
The performance of a model predictive controller depends on the quality of
the plant model that is available. Often parameters in a run-of-mine (ROM)
ore milling circuit are uncertain and inaccurate parameter estimation ...
Sekgota, Mpolaeng Gilbert(University of Pretoria, 2013-05-27)
The Sustainable Restitution Support – South Africa (SRS-SA) program aimed at the development of a post-settlement support model that could be used to support beneficiaries of land reform in South Africa, especially those ...
Since the emergence of systematic science it has been recognized that a natural phenomenon can be described
by different models that vary in their complexity and their ability to capture the details of the features