krige.glm.control {geoRglm} | R Documentation |
This auxiliary function defines options and model for
pois.krige
and binom.krige
.
krige.glm.control(type.krige = "sk", trend.d = "cte", trend.l = "cte", obj.model = NULL, beta, cov.model, cov.pars, kappa, nugget, micro.scale, dist.epsilon = 1e-10, aniso.pars, lambda)
type.krige |
type of prediction to be performed (minimal mean
square error prediction). Options are
"sk" and "ok" corresponding to prediction with fixed
parameters (type.krige = "sk" ), which is the default, or prediction with a uniform
prior on beta (type.krige = "ok" ).
Prediction using a model with covariates can be done by specifying the
covariate model using the arguments trend.d and
trend.l . |
trend.d |
specifies the trend (covariate) values at the data
locations.
See documentation of trend.spatial for
further details.
Default is trend.d = "cte" . |
trend.l |
specifies the trend (covariate) values at prediction
locations. It must be of the same type as for trend.d .
Only used if prediction locations are provided in the argument
locations . |
obj.model |
a list with the model parameters. |
beta |
numerical value of the mean (vector) parameter.
Only used if type.krige="sk" . |
cov.model |
string indicating the name of the model for the
correlation function. Further details in the
documentation for cov.spatial . |
cov.pars |
a vector with the 2 covariance parameters sigma^2, and phi for the underlying Gaussian field. |
kappa |
additional smoothness parameter required by the following correlation
functions: "matern" , "powered.exponential" , "cauchy" and
"gneiting.matern" . |
nugget |
the value of the nugget parameter
tau^2 for the underlying Gaussian field. Default is
nugget = 0 . |
micro.scale |
micro-scale variance. If specified, the
nugget is divided into 2 terms: micro-scale variance
and measurement error.
This has effect on prediction where the ``signal'' part of S
(without the measurement error part of the nugget) is predicted. The
default is micro.scale = nugget . |
dist.epsilon |
a numeric value. Locations which are separated by a distance less than this value are considered co-located. |
aniso.pars |
parameters for geometric anisotropy
correction. If aniso.pars = FALSE no correction is made, otherwise
a two elements vector with values for the anisotropy parameters
must be provided. Anisotropy correction consists of a
transformation of the data and prediction coordinates performed
by the function coords.aniso . |
lambda |
numeric value of the Box-Cox transformation parameter
for pois.krige .
The value lambda = 1 corresponds to
no transformation and lambda = 0 corresponds to
the log-transformation.
Prediction results are back-transformed and
returned is the same scale as for the original data. |
A list with processed arguments to be passed to the main function.
Ole F. Christensen OleF.Christensen@agrsci.dk,
Paulo J. Ribeiro Jr. Paulo.Ribeiro@est.ufpr.br.
pois.krige
and binom.krige
.