Show BayesX Term Options
Description
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.
Usage
1  bayesx.term.options(bs = "ps", method = "MCMC")

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

Details
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 functionread.bnd
andshp2bnd
) as an additional argument namedmap
within functionsx
, or supplied within argumentxt
when using functions
, 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 functionread.bnd
andshp2bnd
) as an additional argument namedmap
(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 functionread.bnd
,read.gra
andshp2bnd
), as an additional argument namedmap
(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 ifmethod = "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.
Author(s)
Nikolaus Umlauf, Thomas Kneib, Stefan Lang, Achim Zeileis.
Examples
1 2 3 4 5 6 