Ez.eqn9.supp {calibrator} | R Documentation |
Expectation as per equation 10 of KOH2001 (not the supplement)
Ez.eqn9.supp(x, theta, d, D1, D2, H1, H2, phi) Ez.eqn9.supp.vector(x, theta, d, D1, D2, H1, H2, phi)
x |
point at which expectation is needed |
theta |
parameters |
d |
observations and code outputs |
D1 |
code run points |
D2 |
observation points |
H1 |
regression function for D1 |
H2 |
regression function for D2 |
phi |
hyperparameters |
The user should always use Ez.eqn9.supp()
, which is a wrapper
for Ez.eqn9.supp.vector()
. The forms differ in their treatment
of theta. In the former, theta must be a
vector; in the latter, theta may be a matrix, in which
case Ez.eqn9.supp.vector()
is applied to the rows.
Note that Ez.eqn9.supp.vector()
is vectorized in x
but
not theta (if given a multi-row object,
apply(theta,1,...)
is used to evaluate the function for each
row supplied).
Function Ez.eqn9.supp()
will take multiple-row arguments for
x
and theta
. The output will be a matrix, with rows
corresponding to the rows of x
and columns corresponding to the
rows of theta
. See the third example below.
Note that function Ez.eqn9.supp()
determines whether there are
multiple values of theta by is.vector(theta)
. If
this returns TRUE
, it is assumed that theta is a
single point in multidimensional parameter space; if FALSE
, it
is assumed to be a matrix whose rows correspond to points in parameter
space.
So if theta is one dimensional, calling
Ez.eqn9.supp()
with a vector-valued theta will
fail because the function will assume that theta is a
single, multidimensional, point. To get round this, use
as.matrix(theta)
, which is not a vector; the rows are the (1D)
parameter values.
Robin K. S. Hankin
data(toys) Ez.eqn9.supp(x=x.toy, theta=theta.toy, d=d.toy, D1=D1.toy, D2=D2.toy, H1=H1.toy,H2=H2.toy, phi=phi.toy) Ez.eqn9.supp(x=D2.toy, theta=t.vec.toy, d=d.toy, D1=D1.toy, D2=D2.toy, H1=H1.toy,H2=H2.toy, phi=phi.toy) Ez.eqn9.supp(x=x.vec, theta=t.vec.toy, d=d.toy, D1=D1.toy, D2=D2.toy, H1=H1.toy,H2=H2.toy, phi=phi.toy)