h.lasso: Define a LASSO Random Hierarchical Component in a Linear...

In joechip90/PaGAn: Paleo-Geography Analysis Package

Define a LASSO Random Hierarchical Component in a Linear Model

Description

Function to specify a LASSO random hierarchical component within a Bayesian model specification. This function is not usually called directly but instead called during processing of the h terms in a hierarchical linear model specification.

Usage

h.lasso(
  var,
  effName = NULL,
  centreCovs = TRUE,
  scaleCovs = TRUE,
  suffix = "",
  iidPrecPrior = "dgamma(0.001, 0.001)"
)

Arguments

var	The variable around which the hierarchical effect will be defined. This can be a data.frame, matrix, or a vector containing the different levels to deine the effect over.
effName	A character scalar giving a name for the hierarchical effect being defined and used as name for the appropriate nodes.
centreCovs	A logical scalar denoting whether the fixed effects in the model should be centred before the analysis: each covariate element is subtracted by its mean. centreCovs can also be a function with one argument that is a vector of covariate values. In this case the variable is instead centred around the output of this function.
scaleCovs	A logical scalar denoting whether the fixed effects in the model should be scaled before the analysis: each covariate element is divided by its standard deviation. scaleCovs can also be a function with one argument that is a vector of covariate values. In this case the variable is instead scaled around the output of this function.
suffix	A character scalar giving an additional suffix applied to all elements created in the hierarchical model specification.
iidPrecPrior	A character scalar containing the NIMBLE code that determines of the distribution of prior specification of the precision parameter in the iid random effect.

Value

A list element with the following named elements:

name

A character scalar containing the name of the hierarchical effect and is used as a name for intermediary variables

code

A character scalar containing the NIMBLE code specifying the hierarchical effect (and will be passed to nimbleCode)

constants

A list containing named elements corresponding to the variables used as constants needed for the hierarchical effect in nimbleModel

data

A list containing named elements corresponding to the data nodes used for the hierarchical effect in nimbleModel

inits

A named list of starting values for model variables used in the hierarchical effect and passed to nimbleModel

monitors

The nodes of the hierarchical effect to monitor in the MCMC and passed to configureMCMC

monitors2

The nodes of the hierarchical effect to monitor in the supplemental chain monitor in the MCMC and passed to configureMCMC

initCode

A list of language objects to run upon initialisation of the NIMBLE instance (see mcmcNIMBLERun)

exitCode

A list of language objects to run upon completion of the NIMBLE instance (see mcmcNIMBLERun)

runTimeGlobal

A list of objects to pass to be compied into each environment of each NIMBLE instance (see mcmcNIMBLERun)

projFunc

A function as produced by the nimbleFunction function that maps the random variables defined by the hierarchical model to the data. If NULL then it is assumed the effect is defined with the same structure as the data already

Author(s)

Joseph D. Chipperfield, [e-mail]

See Also

nimbleCode, mcmcNIMBLERun, configureMCMC, nimbleFunction, h

joechip90/PaGAn documentation built on April 17, 2025, 4:05 p.m.