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Bayesian Vector Autoregression Modeling: BayVAR 1.0

  Date Added: September 15, 2013  |  Visits: 168

Bayesian Vector Autoregression Modeling: BayVAR

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The priors may be: Litterman random walk plus drift prior; Raynauld-Simonato seasonal random walk plus drift prior or Canova prior: seasonal and non-seasonal unit roots via stochastic constraints + Litterman prior. Combination is achieved using Theil-Goldberger mixed estimation.Estimation uses Theil-Goldberger mixed procedure or OLS.Calibration may be performed using axial search.

Requirements: No special requirements
Platforms: Matlab
Keyword: Achieved Axial Estimation Mixed Performed Prior Procedure Search Theilgoldberger
Users rating: 0/10

License: Shareware Size: 184.32 KB
BAYESIAN VECTOR AUTOREGRESSION MODELING: BAYVAR RELATED
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