tgp
function-- the generic interface to treed Gaussian process
modelingtgp.default.params(col, base = "gp")
dim(X)[2]
plus 1base = "gp"
. Future versions of
this package will support other base models.params
..."expsep"
separable power exponential family
correlation model; alternate is "exp"
isotropic power family"bflat"
;
alternates include "b0"
hierarchical Normal prior,
"bmle"
empirical Bayes Normal prior, "bcart"
Bayesian linear CART style prior from Chipman et al, "b0tau"
a independent Normal prior with inverse-gamma variance.c(0.5,0.1,1.0,1.0)
starting values for range $d$,
nugget $g$, $\sigma^2$, and $\tau^2$rep(0,d)
starting values for beta linear parametersc(0.25,2,10)
tree prior process parameters
c(alpha, beta, nmin)
specifying
$$p_{\mbox{\tiny split}}(\eta, \mathcal{T}) =
\alpha*(1+\eta)^\beta$$
with zero probability to trees
with partitions containing less than nmin
data pointsc(5,10)
$\sigma^2$ inverse-gamma prior
parameters c(a0, g0)
where g0
is scale (1/rate) parameterc(5,10)
$\tau^2$ inverse-gamma
prior parameters c(a0, g0)
where g0
is scale (1/rate) parameterc(a1,g1,a2,g2)
where g1
and
g2
are scale (1/rate) parametersc(a1,g1,a2,g2)
where g1
and
g2
are scale (1/rate) parameters; default reduces to simple exponential priorc(10,0.2,10)
Limiting Linear model parameters c(g, t1, t2), with growth parameter g > 0
minimum parameter t1 >= 0
and maximum parameter t1 >= 0
, where
t1 + t2 <= 1<="" code=""> specifies $$p(b|d)=t_1 +
\exp\left{\frac{-g(t_2-t_1)}{d-0.5}\right}$$=>
"fixed"
Hierarchical exponential distribution
parameters to a1
, g1
, a2
, and g2
of the prior distribution for the range parameter d.p
;
fixed indicates that the hierarchical prior is "fixed"
Hierarchical exponential
distribution parameters to a1
, g1
,
a2
, and g2
of the prior distribution for the nug
parameter nug.p
; "fixed"
indicates that the
hierarchical prior is c(0.2,10)
Hierarchical exponential distribution prior for
a0
and g0
of the prior distribution for the s2
parameter s2.p
; "fixed"
indicates that the
hierarchical prior is c(0.2,10)
Hierarchical exponential distribution prior for
a0
and g0
of the prior distribution for the s2
parameter tau2.p
; "fixed"
indicates that the
hierarchical prior is dQuote{turned off}tgp