This function combines the results from the staircase.EM
fit and the
SG method to estimate the hyperparameters associated with the ungauged sites.
1  staircase.hyper.est(emfit, covfit, u, p, g, d0 = NULL)

emfit 
Output from the 
covfit 
The covariance matrix between all locations (with new locations at the beginning). This is an output from the SG fitting 
u 
number of new locations 
p 
dimension of the multivariate response 
g 
number of stations 
d0 
(optional) The degrees of freedom for the new locations (ungauged block) 
List with the following elements:
Delta.0 
The degree of freedoms for the new locations. Equal to

Lambda.0 
Conditional variance between new locations given the gauged stations 
Xi0.0 
the regression slope (Note: τ_{0i} = {\rm kronecker}(ξ_0 , diag(p))) 
H.0 
The variance matrix for the rows of τ^{[u]} 
Also all components of the output of the staircase.EM
fit (for
blocks 1K).
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
All documentation is copyright its authors; we didn't write any of that.