dc.contributor.author |
Gupta, R
|
|
dc.contributor.author |
Das, Sonali
|
|
dc.date.accessioned |
2012-01-11T11:26:00Z |
|
dc.date.available |
2012-01-11T11:26:00Z |
|
dc.date.issued |
2008-10 |
|
dc.identifier.citation |
Gupta, R and Das, S. 2008. Predicting downturns in the US housing market: a Bayesian approach . South African Statistical Association Conference, Pretoria, South Africa, October 27-31, 2008 |
en_US |
dc.identifier.uri |
http://hdl.handle.net/10204/5474
|
|
dc.description |
South African Statistical Association Conference, Pretoria, South Africa, October 27-31, 2008 |
en_US |
dc.description.abstract |
Bayesian methods are influenced by choice of prior. None-the-less, their importance cannot be disregarded in light of current exercise and existing other literature . The way forward is to try other large scale Bayesian models that incorporate other potential fundamentals. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
SASA 2008 |
en_US |
dc.relation.ispartofseries |
Workflow request;1121 |
|
dc.subject |
Bayesian Vector Autoregressive Models |
en_US |
dc.subject |
Statistics |
en_US |
dc.subject |
US housing market |
en_US |
dc.title |
Predicting downturns in the US housing market: a Bayesian approach [Conference presentation] |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.identifier.apacitation |
Gupta, R., & Das, S. (2008). Predicting downturns in the US housing market: a Bayesian approach [Conference presentation]. SASA 2008. http://hdl.handle.net/10204/5474 |
en_ZA |
dc.identifier.chicagocitation |
Gupta, R, and Sonali Das. "Predicting downturns in the US housing market: a Bayesian approach [Conference presentation]." (2008): http://hdl.handle.net/10204/5474 |
en_ZA |
dc.identifier.vancouvercitation |
Gupta R, Das S, Predicting downturns in the US housing market: a Bayesian approach [Conference presentation]; SASA 2008; 2008. http://hdl.handle.net/10204/5474 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Gupta, R
AU - Das, Sonali
AB - Bayesian methods are influenced by choice of prior. None-the-less, their importance cannot be disregarded in light of current exercise and existing other literature . The way forward is to try other large scale Bayesian models that incorporate other potential fundamentals.
DA - 2008-10
DB - ResearchSpace
DP - CSIR
KW - Bayesian Vector Autoregressive Models
KW - Statistics
KW - US housing market
LK - https://researchspace.csir.co.za
PY - 2008
T1 - Predicting downturns in the US housing market: a Bayesian approach [Conference presentation]
TI - Predicting downturns in the US housing market: a Bayesian approach [Conference presentation]
UR - http://hdl.handle.net/10204/5474
ER -
|
en_ZA |