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.
bayesx.term.options(bs = "ps", method = "MCMC")
character, the term specification for which controlling parameters should be shown.
character, for which method should additional arguments be shown, options are
"MCMC"
, "REML"
and "STEP"
.
Nikolaus Umlauf, Thomas Kneib, Stefan Lang, Achim Zeileis.
At the moment the following model terms are implemented, for which additional controlling parameters may be specified:
"rw1"
, "rw2"
: Zero degree P-splines: Defines a zero degree P-spline with first or
second order difference penalty. A zero degree P-spline typically
estimates for every distinct covariate value in the dataset a separate
parameter. Usually there is no reason to prefer zero degree P-splines
over higher order P-splines. An exception are ordinal covariates or
continuous covariates with only a small number of different values.
For ordinal covariates higher order P-splines are not meaningful while
zero degree P-splines 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"
: P-spline with first or second order
difference penalty.
"te"
, "pspline2dimrw1"
: Defines a two-dimensional P-spline based on the tensor
product of one-dimensional P-splines with a two-dimensional 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 two-dimensional P-splines with a
two-dimensional 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 multi-state
models: Defines a P-spline with second order random walk penalty for the parameters of
the spline for the log-baseline effect \(log(\lambda(time))\).
"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
shrinkage-prior for the corresponding parameters
\(\gamma_j\), \(j = 1, \ldots, q\), \(q \geq 1\) of the
linear effects \(x_1, \ldots, x_q\). 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.
## show arguments for P-splines
bayesx.term.options(bs = "ps")
bayesx.term.options(bs = "ps", method = "REML")
## Markov random fields
bayesx.term.options(bs = "mrf")
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