Description Usage Arguments Details Value Author(s) References See Also Examples
Computes envelope for empirical covariogram by simulating data for given model parameters. This function is for the Poisson-log normal model.
1 2 3 4 |
covariog.model.env(geodata, coords = geodata$coords, units.m = "default",
obj.covariog, model.pars, nsim = 500, prob = c(0.025, 0.975),
messages)
|
geodata |
a list containing element |
coords |
an n x 2 matrix, each row containing
Euclidean coordinates of the n data locations. By default it takes the
element |
units.m |
n-dimensional vector of observation times for the data. By default ( |
obj.covariog |
an object of the class |
model.pars |
a list with model specification and parameter values. The required components of the list are:
|
nsim |
number of simulations used to compute the envelope. Default is |
prob |
the quantiles used for constructing the envelopes. Default is 2.5% and 97.5% |
messages |
logical. If |
The envelope is computed assuming a Poisson-log normal model. Simulated values are generated at the data locations, given the model parameters. The empirical covariogram is computed for each simulation using the same binning as for the original covariogram of the data. The envelope is computed by taking, at each lag, the quantile-values of the covariograms for the simulated data.
An object of the class "covariogram.envelope"
which is a
list with the components:
u |
a vector with distances. |
v.lower |
a vector with the upper-quantile covariogram values for each
distance in |
v.upper |
a vector with the lower-quantile covariogram values for each
distance in |
Ole F. Christensen OleF.Christensen@agrsci.dk,
Paulo J. Ribeiro Jr. Paulo.Ribeiro@est.ufpr.br.
Further information about geoRglm can be found at:
http://gbi.agrsci.dk/~ofch/geoRglm.
covariog
for covariogram calculation and plot.covariogram
for graphical output.
1 2 3 4 5 6 7 8 9 | data(p50)
covar <- covariog(p50, uvec = c(1:10))
parmval <- list(cov.model = "exponential", cov.pars = c(0.8,0.1),
beta = 1)
class(parmval) <- "covariomodel"
konvol <- covariog.model.env(p50, obj.covariog = covar,
model.pars = parmval)
plot(covar, envelope.obj = konvol)
lines(parmval, max.dist = 10, lty = 1)
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