Show BayesX Term Options

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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

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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 "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 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(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 shrinkage-prior 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

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## 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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