pffrSim: Simulate example data for pffr
Description
Simulates example data for pffr from a variety of terms.
Scenario "all" generates data from a complex multivariate model $$Y_i(t)
= \mu(t) + \int X_{1i}(s)\beta_1(s,t)ds + xlin \beta_3(t) + f(xte1, xte2) +
f(xsmoo, t) + \beta_4 xconst + \epsilon_i(t)$$. Scenarios "int", "ff", "lin",
"te", "smoo", "const" generate data from simpler models containing only the
respective term(s) in the model equation given above. Specifiying a
vector-valued scenario will generate data from a combination of the
respective terms. Sparse/irregular response trajectories can be generated by
setting propmissing to something greater than 0 (and smaller than 1).
The return object then also includes a ydata-item with the sparsified
data.Usage
pffrSim(scenario = "all", n = 100, nxgrid = 40, nygrid = 60, SNR = 10,
propmissing = 0, limits = NULL)
Arguments
nxgrid
number of evaluation points of functional covariates
nygrid
number of evaluation points of the functional response
SNR
the signal-to-noise ratio for the generated data: empirical
variance of the additive predictor divided by variance of the errors.
propmissing
proportion of missing data in the response, default = 0.
See Details.
limits
a function that defines an integration range, see
ff Value
- a named list with the simulated data, and the true components of the
predictor etc as attributes.
Details
See source code for details.