sim.cred.band {credsubs}  R Documentation 
sim.cred.band
returns a simultaneous band over a finite set of
covariate points given either a sample from the posterior of the
regression surface or a function FUN(x, params)
and a sample from
the posterior of the parameters.
sim.cred.band(
params,
design = NULL,
FUN = function(x, params) { params %*% t(x) },
cred.level = 0.95,
method = c("asymptotic", "quantile"),
sides = c("both", "upper", "lower"),
est.FUN = mean,
var.FUN = sd,
point.estimate = NULL,
track = numeric(0),
verbose = FALSE
)
params 
A numeric matrix whose rows are draws from the posterior distribution of either the regression surface or the parameter vector. 
design 
(Optional) A numeric matrix whose rows are covariate points over which the band is to be constructed. 
FUN 
(Optional) a function of the form 
cred.level 
Numeric; the credible level. 
method 
Either "asymptotic" (default) or "quantile"; see details. 
sides 
One of "both" (default), "upper", or "lower". Which bounds should be constructed? 
est.FUN 
The function used to produce estimates of the regression
surface. Default is 
var.FUN 
The function used to quantify the variability of the
regression surface posterior. Default is 
point.estimate 
If not null, replaces the mean and sets the reference
around which the standard error is computed.
Useful for bootstrapping methods.
Treated as a row of the 
track 
A numeric vector of indices indicating which rows (default none)
of the design matrix should have the sample of the corresponding

verbose 
Logical (default 
If design
is NULL
(default), it is taken to be the identity
matrix of dimension ncol(params)
, so that the rows of params
are treated as draws from the posterior FUN(x, params)
.
The 'asymptotic' method assumes that the marginal posteriors of
the FUN(x, params)
are asymptotically normal and is usually
significantly faster and less memoryintensive than the 'quantile'
method, which makes no such assumption.
An object of class sim.cred.band
, which contains:
upper
A numeric vector of upper bounds.
lower
A numeric vector of lower bounds.
cred.level
As provided.
method
As provided.
sides
As provided.
est
Posterior estimate of the regression surface.
est.FUN
As provided.
var
Summary of posterior variability of the regression surface.
var.FUN
As provided.
W
An estimate of the extremal errors.
W.crit
The critical quantile of W.
trace
The posterior samples of the regression surface
indicated by the track
argument.
### Sample from regression surface posterior
reg.surf.sample < matrix(rnorm(1000, mean=1:10), ncol=2, byrow=TRUE)
sim.cred.band(reg.surf.sample, cred.level=0.80)
### Parametric case
design < cbind(1, 1:10)
params < matrix(rnorm(200, mean=1:2), ncol=2, byrow=TRUE)
sim.cred.band(params, design)
### With custom function
params.sd < cbind(1 / rgamma(100, 1), params)
FUN.sd < function(x, params) { params[, 1] %*% t(x) / params[, 1] }
sim.cred.band(params.sd, design, FUN.sd)