R2BayesX (version 0.1-2)

bayesx.term.options: 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

bayesx.term.options(bs = "ps", method = "MCMC")

Arguments

bs

the term specification for which controlling parameters should be shown.

method

for which method should additional arguments be shown, options are "MCMC", "REML" and "STEP".

Details

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 functionread.bndandshp2bnd) as an additional argument namedmapwithin functionsx, or supplied within argumentxtwhen using functions, 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 functionread.bndandshp2bnd) 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.graandshp2bnd), as an additional argument namedmap(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": SpecialBayesXspecifier 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 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.

Examples

## 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")