Time-varying coefficient structure

Specify a time-varying coefficient (TVC): one or more fixed-effect coefficients are allowed to evolve over time, with the evolution governed by a temporal prior (rw1, rw2, ar1, or a GP).

Usage

temporal_tvc(
  time_var,
  terms = 1,
  structure = c("rw1", "rw2", "ar1", "gp"),
  group_var = NULL,
  shared = NULL,
  sigma_prior_U = 1,
  sigma_prior_alpha = 0.01
)

Arguments

time_var

Single character string naming the time variable in the data.

terms

Which coefficients vary over time. A formula, an integer vector of design-matrix column indices, or a character vector of term names. Default 1 (the intercept).

structure

Temporal prior governing how the coefficients evolve. One of "rw1", "rw2", "ar1", or "gp".

group_var

Optional character string naming a grouping variable for group-specific time-varying coefficients.

shared

Whether the effect is shared across processes in a multi-process model. NULL (default) shares it; FALSE fits process-specific effects and emits a warning.

sigma_prior_U, sigma_prior_alpha

Penalized-complexity prior on each varying coefficient's marginal standard deviation, calibrated so that P(sigma > sigma_prior_U) = sigma_prior_alpha. Defaults to P(sigma > 1) = 0.01. sigma_prior_U must be positive and sigma_prior_alpha must lie in (0, 1).

Value

A tulpa_tvc object.

See also

temporal_rw1(), temporal_rw2(), temporal_ar1() for the underlying temporal priors.

Examples

# Intercept that drifts as a first-order random walk over year
temporal_tvc("year", structure = "rw1")