Group Assessment of Multivariate Prior Distributions
Article Abstract:
The generation of subjective prior distributions for p-dimensional unobservables is featured in the context of multivariate prior distribution reflecting blended perspectives of some important association. The preferred approach involves a group of p questions administered to N subjects on a homogeneous panel of randomly chosen experts. Every subject responds to questions dealing with only one-dimensional parameters. Toward this effect, a multistage qualitative controlled feed back interrogation method is employed. N p vector responses from the experts are blended to achieve multivariate subjective prior density for p-dimension. Experts are defined as individuals with contextual information of substantive matters, and they may well share the same bias. Individual responses will have mutual correlation. Matrix constants are explained in light of continuous probability. Former research on univariate prior distributions did not lend itself to assessing prior distributions. Sources for that research are included. A model for single stage elicitation is developed. The Bayes theorem is employed to find posterior inference. Convergence and additional fractiles are also considered.
Publication Name: Technological Forecasting & Social Change
Subject: Social sciences
ISSN: 0040-1625
Year: 1983
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The Brain, the Mind and the Future
Article Abstract:
Physiological research has generally aimed at examining past phenomena. Such a retrospective has contributed to theory fragmentation in the sciences, as well as a lack of guidance in global matters. Brain research and the psychology of consciousness is a necessary area of further investigation, as are artificial intelligence and systems analysis problems. Frontal brain research by Luria and Pribram is considered. Hemispheric research, by Sperry and Bogen is analyzed and Von Newmann's investigations in artificial intelligence is reviewed. The prediction task is examined from philosophical and psychological levels. A model of brain functioning and forecasting is supported by field studies and cybernetic research. The roles of the brain's hemispheres are discussed. Balanced mind, aspects of model, as identified by the Langley Porter Institute of the University of California at the San Francisco Medical School, are highlighted, as are tables of regression analysis data.
Publication Name: Technological Forecasting & Social Change
Subject: Social sciences
ISSN: 0040-1625
Year: 1983
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Long-term forecasting of noncointegrated and cointegrated regional and national models
Article Abstract:
The application of Johansen's multivariate test for cointegration on four five-variable state models and one three-variable national model was examined as part of a study on the long-term forecasting of cointegrated and noncointegrated multivariate systems. Results revealed that forecasting accuracy is significantly enhanced by the application of multivariate cointegration and error correction methods. In addition, results showed that accuracy can be enhanced using error correction mechanism models with two to three variables.
Publication Name: Journal of Regional Science
Subject: Social sciences
ISSN: 0022-4146
Year: 1995
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