BayesX model terms specified using functions sx
may have
additional optional control arguments. Therefore function
bayesx.term.options
displays the possible additional controlling parameters for a
particular model term.
1  bayesx.term.options(bs = "ps", method = "MCMC")

bs 
character, the term specification for which controlling parameters should be shown. 
method 
character, for which method should additional arguments be shown, options are

At the moment the following model terms are implemented, for which additional controlling parameters may be specified:
"rw1"
, "rw2"
: Zero degree Psplines: Defines a zero degree Pspline with first or
second order difference penalty. A zero degree Pspline typically
estimates for every distinct covariate value in the dataset a separate
parameter. Usually there is no reason to prefer zero degree Psplines
over higher order Psplines. An exception are ordinal covariates or
continuous covariates with only a small number of different values.
For ordinal covariates higher order Psplines are not meaningful while
zero degree Psplines might be an alternative to modeling nonlinear
relationships via a dummy approach with completely unrestricted
regression parameters.
"season"
: Seasonal effect of a time scale.
"ps"
, "psplinerw1"
, "psplinerw2"
: Pspline with first or second order
difference penalty.
"te"
, "pspline2dimrw1"
: Defines a twodimensional Pspline based on the tensor
product of onedimensional Psplines with a twodimensional first order random walk
penalty for the parameters of the spline.
"kr"
, "kriging"
: Kriging with stationary Gaussian random fields.
"gk"
, "geokriging"
: Geokriging with stationary Gaussian random fields: Estimation
is based on the centroids of a map object provided in
boundary format (see function read.bnd
and shp2bnd
) as an additional
argument named map
within function sx
, or supplied within argument
xt
when using function s
, e.g., xt = list(map = MapBnd)
.
"gs"
, "geospline"
: Geosplines based on twodimensional Psplines with a
twodimensional first order random walk penalty for the parameters of the spline.
Estimation is based on the coordinates of the centroids of the regions
of a map object provided in boundary format (see function read.bnd
and
shp2bnd
) as an additional argument named map
(see above).
"mrf"
, "spatial"
: Markov random fields: Defines a Markov random field prior for a
spatial covariate, where geographical information is provided by a map object in
boundary or graph file format (see function read.bnd
, read.gra
and
shp2bnd
), as an additional argument named map
(see above).
"bl"
, "baseline"
: Nonlinear baseline effect in hazard regression or multistate
models: Defines a Pspline with second order random walk penalty for the parameters of
the spline for the logbaseline effect log(λ(time)).
"factor"
: Special BayesX specifier for factors, especially meaningful if
method = "STEP"
, since the factor term is then treated as a full term,
which is either included or removed from the model.
"ridge"
, "lasso"
, "nigmix"
: Shrinkage of fixed effects: defines a
shrinkageprior for the corresponding parameters
γ_j, j = 1, …, q, q ≥q 1 of the
linear effects x_1, …, x_q. There are three
priors possible: ridge, lasso and Normal Mixture
of inverse Gamma prior.
"re"
: Gaussian i.i.d. Random effects of a unit or cluster identification covariate.
Nikolaus Umlauf, Thomas Kneib, Stefan Lang, Achim Zeileis.
1 2 3 4 5 6  ## show arguments for Psplines
bayesx.term.options(bs = "ps")
bayesx.term.options(bs = "ps", method = "REML")
## Markov random fields
bayesx.term.options(bs = "mrf")

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