Predict method for LAME models — predict.lame • lame

Generate predictions from a fitted longitudinal AME model. Returns a list of matrices (one per time point) on the requested scale.

Usage

# S3 method for class 'lame'
predict(
  object,
  newdata = NULL,
  type = c("response", "link"),
  h = 0L,
  by_draw = FALSE,
  interval = c("none", "credible"),
  probs = c(0.025, 0.975),
  newexposure = NULL,
  n_draws = NULL,
  seed = NULL,
  ...
)

Arguments

object: Fitted LAME model object.
newdata: Optional list of T dyadic covariate arrays ([n_row, n_col, p] each, with the same actors as the fit) to compute counterfactual predictions. When NULL, the training-data predictions are returned.
type: Character; "response" (default) or "link".
h: Integer >= 0: forecast horizon. When h = 0 (default), returns in-sample predictions as before. When h > 0, propagates the AR(1) (or RW1) state-space model forward by h periods and returns a list of h matrices (one per future period). Requires at least one dynamic component on the fit. Warns when posterior $\rho_\beta$ is near 1.
by_draw: When TRUE and h > 0, returns an n x n x h x n_draws array of per-draw forecasts instead of per-period means.
interval: One of "none" (default) or "credible". When h > 0 and "credible", the per-period output is a list of length-3 lists with $lower, $median, $upper matrices computed at the probs quantiles across posterior draws. Ignored for in-sample (h = 0) predictions.
probs: Length-2 vector of lower / upper quantiles for the credible interval when interval = "credible". Default c(0.025, 0.975).
newexposure: Optional length-h non-negative numeric vector of future-period exposures (Poisson only). When omitted and the fit has period_exposure stored, defaults to the last observed exposure; when both are absent, defaults to 1.
n_draws: Number of posterior draws to use when h > 0. Default NULL uses all stored draws. Ignored for in-sample (h = 0) predictions.
seed: Optional RNG seed for the h > 0 forecast draws, making forecasts reproducible. Ignored when h = 0.
...: Additional arguments (not used).

Value

List of prediction matrices (one per time point).