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36696
2007 May 09
1
generalized least squares with empirical error covariance matrix
I have a bayesian hierarchical normal regression model, in which the
regression coefficients are nested, which I've wrapped into one
regression framework, y = X %*% beta + e . I would like to run data
through the model in a filter style (kalman filterish), updating
regression coefficients at each step new data can be gathered. After
the first filter step, I will need to be able to feed