cov.p5.supp {calibrator} | R Documentation |
Covariance function for posterior distribution of z(.) conditional on estimated hyperparameters and calibration parameters theta.
Cov.eqn9.supp(x, xdash=NULL, theta, d, D1, D2, H1, H2, phi) cov.p5.supp (x, xdash=NULL, theta, d, D1, D2, H1, H2, phi)
x |
first point, or (Cov.eqn9.supp() ) a matrix whose rows
are the points of interest |
xdash |
The second point, or (Cov.eqn9.supp() )
a matrix whose rows are the points of interest. The default of
NULL means to use xdash=x |
theta |
Parameters. For Cov.eqn9.supp() , supply a vector
which will be interpreted as a single point in parameter space. For
cov.p5.supp() , supply a matrix whose rows will be interpreted
as points in parameter space |
d |
Observed values |
D1 |
Code run design matrix |
D2 |
Observation points of real process |
H1 |
Basis function for D1 |
H2 |
Basis function for D2 |
phi |
Hyperparameters |
Evaluates the covariance function: the last formula on page 5 of the supplement. The two functions documented here are vectorized differently.
Function Cov.eqn9.supp()
takes matrices for arguments x
and xdash
and a single vector for theta
. Evaluation is
thus taken at a single, fixed value of theta
. The function
returns a matrix whose rows correspond to rows of x
and whose
columns correspond to rows of xdash
.
Function cov.p5.supp()
takes a vector for arguments x
and
xdash
and a matrix for argument theta
whose rows are the
points in parameter space. A vector V
, with elements
corresponding to the rows of argument theta
is returned:
V[i] = cov(z(x),z(x')|theta[i])
Returns a matrix of covariances
May return the transpose of the desired object
Robin K. S. Hankin
data(toys) x <- rbind(x.toy,x.toy+1,x.toy,x.toy,x.toy) rownames(x) <- letters[1:5] xdash <- rbind(x*2,x.toy) rownames(xdash) <- LETTERS[1:6] Cov.eqn9.supp(x=x,xdash=xdash,theta=theta.toy,d=d.toy,D1=D1.toy,D2=D2.toy,H1=H1.toy,H2=H2.toy,phi=phi.toy) phi.true <- phi.true.toy(phi=phi.toy) Cov.eqn9.supp(x=x,xdash=xdash,theta=theta.toy,d=d.toy,D1=D1.toy,D2=D2.toy,H1=H1.toy,H2=H2.toy,phi=phi.true) # Now try a sequence of thetas: cov.p5.supp(x=x.toy,theta=t.vec.toy,d=d.toy,D1=D1.toy,D2=D2.toy,H1=H1.toy,H2=H2.toy,phi=phi.toy)