nimbleMacros (version 0.1.1)

setPriors: Set up prior values for different categories of nodes

Description

Generates a list of custom specifications of priors for parameters in the model. It is possible to set priors for a category of parameters (e.g., intercept, coefficient, sd, factor, continuous) or to set a prior for a specific parameter name (optionally including brackets with indices).

Usage

setPriors(
  intercept = quote(dnorm(0, sd = 1000)),
  coefficient = quote(dnorm(0, sd = 1000)),
  sd = quote(dunif(0, 100)),
  factor = NULL,
  continuous = NULL,
  lkjShape = 1,
  ...
)

Value

A named list of prior specifications to be passed to the priors

argument of other macros in the package, such as LINPRED.

Arguments

intercept

Prior specification for intercepts

coefficient

Prior specfication for slope coefficients

sd

Prior specification for random effects SDs

factor

Prior specifications for slope coefficients corresponding to factor data

continuous

Prior specifications for slope coefficients corresponding to continuous data

lkjShape

Value of shape parameter for LKJ distribution prior, used for correlation matrix in correlated random slope and intercept models

...

Specific parameters, optionally with brackets/indices

Author

Ken Kellner

Details

Exact name matches including brackets/indices are used first, followed by name matches without indices, followed by data type (factor/continuous) followed by parameter type (intercept/coefficient/sd). Arguments can be supplied as quoted code, a character string, or as a list of prior components. For example, to specify the prior dnorm(0, sd = 10) you could specify quote(dnorm(0, sd = 10)), or "dnorm(0, sd = 10)", or list("dnorm", 0, sd = 10).

See Also

[nimble::dlkj_corr_cholesky] for more on the LKJ distribution

Examples

# Set a prior for intercept terms using quoted code
setPriors(intercept = quote(dunif(-5,5)))
# Instead using a character string
setPriors(intercept = "dunif(-5,5)")
# Set prior for slopes associated with factor covariates
setPriors(factor = quote(dnorm(0, sd = 2.5)))
# Set prior for a specific coefficient
setPriors('alpha[1]' = "dnorm(0, 3)")