Description Usage Arguments Details Value Author(s) See Also Examples
Generate empirical Bayes regularization (priors) and choose initial values and ranges for (isotropic) lengthscale and nugget parameters to a Gaussian correlation function for a GP regression model
1 2 
d 
can be 
g 
can be 
X 
a 
y 
a vector of responses/dependent values 
samp.size 
a scalar integer indicating a subset size of 
These functions use aspects of the data, either X
or y
,
to form weakly informative default priors and choose initial values
for a lengthscale and nugget parameter. This is useful since the
likelihood can sometimes be very flat, and even with proper priors
inference can be sensitive to the specification of those priors
and any initial search values. The focus here is on avoiding pathologies
while otherwise remaining true to the spirit of MLE calculation.
darg
output specifies MLE inference (out$mle = TRUE
)
by default, whereas garg
instead fixes the nugget at the starting value,
which may be sensible for emulating deterministic computer simulation data;
when out$mle = FALSE
the calculated range outputs c(out$min, out$max)
are set to dummy values that are ignored in other parts of the laGP package.
darg
calculates a Gaussian distance matrix between all pairs of
X
rows, or a subsample of rows of size samp.size
. From
those distances it chooses the range and start values from the range
of (nonzero) distances and the 0.1
quantile, respectively.
The Gamma prior values have a shape of out$a = 3/2
and a rate
out$b
chosen by the incomplete Gamma inverse function to put
0.95
probability below out$max
.
garg
is similar except that it works with (y mean(y))^2
instead of the pairwise distances of darg
. The only difference
is that the starting value is chosen as the 2.5% quantile.
Both functions return a list containing the following entries. If the
input object (d
or g
) specifies one of the values then
that value is copied to the same list entry on output. See the
Details section for how these values are calculated
mle 
by default, 
start 
starting value chosen from the quantiles of

min 
minimum value in allowable range for the parameter  for future inference purposes 
max 
maximum value in allowable range for the parameter  for future inference purposes 
ab 
shape and rate parameters specifying a Gamma prior for the parameter 
Robert B. Gramacy [email protected]
vignette("laGP")
,
laGP
, aGP
,
mleGP
, distance
, llikGP
1 2 3 4 5 6 7 8 
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.