pffrSim: Simulate example data for pffr (deprecated)

Description

**Deprecated**

`pffrSim()` was renamed to [pffr_simulate()] for consistency with the package naming conventions.

Usage

pffrSim(
  formula = NULL,
  scenario = NULL,
  n = 100,
  nxgrid = 40,
  nygrid = 60,
  yind = NULL,
  xind = NULL,
  data = NULL,
  effects = list(),
  intercept = "beta",
  SNR = 10,
  family = gaussian(),
  propmissing = 0,
  limits = NULL,
  seed = NULL,
  wiggliness = 1,
  k_truth = list()
)

Value

Same as pffr_simulate.

Arguments

formula: A formula specifying the model structure (e.g., Y ~ ff(X1) + xlin). If provided, the scenario argument is ignored.
scenario: Deprecated. Character string or vector specifying predefined scenarios. Use the formula argument instead.
n: Number of observations.
nxgrid: Number of evaluation points for functional covariates. Ignored if xind is provided.
nygrid: Number of evaluation points for the functional response. Ignored if yind is provided.
yind: Numeric vector of evaluation points for the response. Defaults to seq(0, 1, length.out = nygrid).
xind: Numeric vector of evaluation points for functional covariates. Defaults to seq(0, 1, length.out = nxgrid).
data: Optional data frame with pre-generated covariates.
effects: Named list mapping term labels to effect specifications. Each entry can be a preset name (e.g., "cosine"), a function, or a numeric value. See Details.
intercept: Intercept specification: preset name ("beta", "constant", "sine", "zero"), a function of t, or a numeric value.
SNR: Signal-to-noise ratio: var(eta) / var(epsilon).
family: A family object for the response distribution. Defaults to gaussian().
propmissing: Proportion of missing data in the response (0 to 1).
limits: A function defining integration limits for ff() terms, e.g., function(s, t) s < t.
seed: Optional random seed for reproducibility.
wiggliness: Controls smoothness for the "random" preset (default: 1). Higher values produce more wiggly truth functions. Typical range: 0.001 (very smooth) to 10 (very wiggly).
k_truth: Named list of basis dimensions for random truth generation. Defaults: list(ff_s = 8, ff_t = 8, smooth_z = 8, smooth_t = 8, linear = 8, intercept = 8, concurrent = 8).