Computes envelopes for a empirical variogram by simulating data for given model parameters.
Computes bootstrap paremeter estimates
variog.model.env(geodata, coords = geodata$coords, obj.variog,
model.pars, nsim = 99, save.sim = FALSE, messages)boot.variofit(geodata, coords = geodata$coords, obj.variog,
model.pars, nsim = 99, trace = FALSE, messages)
a list containing element coords
as described next. Typically an object of the class
"geodata"
- a geoR data-set.
If not provided the argument
coords
must be provided instead.
an \(n \times 2\) matrix, each row containing
Euclidean
coordinates of the n data locations. By default it takes the
element coords
of the argument geodata
.
an object of the class "variogram"
, typically
an output of the function variog
.
a list with model specification and parameter
values. The input is typically an object of the class
variomodel
which is an output of likfit
,
variofit
.
The required components of the list are:
beta
, the mean parameter. Defaults to zero.
cov.model
, the covariance model. Defaults to
"exponential".
cov.pars
, the covariance parameters
\(\sigma^2\) and \(\phi\).
kappa
, the extra covariance parameters for some of the
covariance models. Defaults to \(0.5\).
nugget
, the error component variance. Defaults to zero.
estimator.type
, the type of variogram
estimator. Options for "classical"
and
"robust"
. Defaults to obj.variog$estimator
.
number of simulations used to compute the envelopes. Defaults to 99.
logical. Indicates whether or not the simulated data
are included in the output. Defaults to FALSE
.
logical. If TRUE
the fitted values for the
bootstrap parameter estimation are printend while the function is
running.
logical. If TRUE
, the default, status messages
are printed while the function is running.
An object of the class
"variogram.envelope"
which is a
list with the components:
a vector with distances.
a vector with the minimum variogram values at each
distance in u
.
a vector with the maximum variogram values at each
distance in u
.
a matrix with the simulated data.
Only returned if save.sim = TRUE
.
The envelopes are computed assuming a (transformed) Gaussian random field model. Simulated values are generated at the data locations, given the model parameters. The empirical variogram is computed for each simulation using the same lags as for the original variogram of the data. The envelopes are computed by taking, at each lag, the maximum and minimum values of the variograms for the simulated data.
Further information on the package geoR can be found at: http://www.leg.ufpr.br/geoR.
variog.mc.env
for envelops computed by
using data permutation,
variog
for variogram calculations,
plot.variogram
and variog.mc.env
for
graphical output. The functions
likfit
, variofit
are used to estimate the model parameters.
# NOT RUN {
s100.ml <- likfit(s100, ini = c(0.5, 0.5), fix.nugget = TRUE)
s100.vario <- variog(s100, max.dist = 1)
s100.env <- variog.model.env(s100, obj.v = s100.vario,
model.pars = s100.ml)
plot(s100.vario, env = s100.env)
# }
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