Calculates the maximum correlations possible consistent with the roughness parameters
ss(A, B, Ainv, Binv)
ss_matrix(hp,useM=TRUE)
ss_matrix_simple(hp,useM=TRUE)
Function ss()
returns a scalar, ss_matrix()
a matrix
of covariances.
Positive-definite matrices (roughness parameters)
The inverses of A
and B
; if missing, compute explicitly
An object of class mhp
Boolean, with default TRUE
meaning to multiply
(pointwise) by \(M\) and FALSE
meaning not to (so giving the
maximum correlation consistent with the roughness matrices \(B\))
Robin K. S. Hankin
Function ss()
calculates the maximum possible correlation
between observations of two Gaussian processes at the same point
(equation 24 of the vignette):
| ( 12B_r+12B_s12B_r^-1 )( 12B_r^-1+12B_s^-1 ) |^-1/4 equation 24 of the vignette
Functions ss_matrix()
and ss_matrix_simple()
calculate
the maximum covariances among the types of object specified in the
hp
argument, an object of class mhp
. Function
ss_matrix()
is the preferred form; function
ss_matrix_simple()
is a less efficient, but more transparent,
version. The two functions should return identical output.
data(mtoys)
ss_matrix(toy_mhp)
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