GHRmodel (version 0.1.1)

crossbasis_inla: Create a Two-Dimensional INLA-compatible Cross-basis Matrix

Description

This function is a wrapper around dlnm::crossbasis to generate cross-basis matrices that capture nonlinear effects of a predictor across both exposure and lag dimensions. The input covariate is passed as a numeric matrix of lagged values, and the resulting columns can be renamed via basis_name for easier reference in model formulas.

Usage

crossbasis_inla(
  covariate,
  basis_name,
  lag,
  argvar = list(),
  arglag = list(),
  ...
)

Value

An object of class "crossbasis_inla" (also inheriting class "crossbasis"), as returned by dlnm:crossbasis() but with customized column names.

Arguments

covariate

A numeric matrix of covariate values. Typically this will be a matrix of lagged covariate values (which can be generated using lag_cov).

basis_name

A character string specifying the prefix for the spline columns in the resulting basis matrix (replacing the default "v").

lag

A numeric vector with min and max lag of the matrix (as in crossbasis).

argvar

A list specifying the shape of the exposure-response function (as in crossbasis).

arglag

A list specifying the shape of the lag-response function (as in crossbasis).

...

Additional arguments passed to dlnm::crossbasis, such as df, degree, knots, etc.

Examples

# Build cross-basis with a custom prefix for columns

# Import example data set 
data("dengue_MS")

lag_mat <- lag_cov(data = dengue_MS,
  name = c("tmin"),
  time = "date",
  lag = c(1:6),
  group = "micro_code",
  add = FALSE) # add = FALSE return only the lagged matrix
  
cb_inla <- crossbasis_inla(
  covariate  = lag_mat,
  basis_name = "tempLag",
  lag = c(1,6),
  argvar = list(fun = "bs", df = 3),
  arglag = list(fun = "poly", degree = 2)
)

# Check class of the cross-basis object
class(cb_inla)

# View resulting cross-basis matrix
head(colnames(cb_inla))