Create Spatially or Temporally Varying Effects for INLA

Description

This function transforms covariates identified by pattern or name into varying effect terms of the form:f(unit, covariate, model = 'iid'), which allows covariates to have varying slopes across spatial or temporal units. The output can be used directly in the covariates argument of write_inla_formulas.

cov_varying(
  covariates,
  unit,
  pattern = NULL,
  name = NULL,
  model = "iid",
  constr = FALSE,
  add = FALSE
)

Arguments

  • covariates: A character vector or a list of character vectors of covariate names. Typically output from cov_multi, cov_uni, or extract_names.
  • unit: Character string specifying the unit of variation (e.g., "spat_id", "year").
  • pattern: A character vector specifying the prefix pattern(s) to match (e.g., “tmin” matches “tmin”, “tmin.l1”, etc.) for transformation.
  • name: Character vector of exact variable names to be transformed.
  • model: Character string specifying the INLA model for the varying effect. Currently, only "iid" is supported.
  • constr: Logical. If TRUE it will impose a sum-to-zero constraint to the random effect. Default is FALSE.
  • add: Logical; if TRUE, appends the transformed covariates to the original ones. Default is FALSE.

Details

  • Use pattern or name (or both) to specify which covariates to transform.
  • The resulting terms use INLA’s f() syntax: f(unit, covariate, model = "iid").
  • Currently only supports "iid" models for varying effects.

Returns

A list of character vectors, each including covariates with varying effects. The output is suitable as input for write_inla_formulas.

Examples

data <- data.frame(tmin.l1 = rnorm(10), pdsi.l1 = rnorm(10))

covs <- extract_names(data, pattern = c("tmin", "pdsi"))
covlist <- cov_multi(covs, pattern = c("tmin", "pdsi"))

# Apply varying effect to tmin
cov_varying(covlist, pattern = "tmin", unit = "spat_id")

# Keep original and add varying effect terms
cov_varying(covlist, pattern = "tmin", unit = "spat_id", add = TRUE)