simulate: Simulate from the posterior distribution of a GAM

In gavinsimpson/gratia: Graceful 'ggplot'-Based Graphics and Other Functions for GAMs Fitted Using 'mgcv'

Simulate from the posterior distribution of a GAM

Description

Simulations from the posterior distribution of a fitted GAM model involve computing predicted values for the observation data for which simulated data are required, then generating random draws from the probability distribution used when fitting the model.

Usage

## S3 method for class 'gam'
simulate(
  object,
  nsim = 1,
  seed = NULL,
  data = newdata,
  weights = NULL,
  ...,
  newdata = NULL
)

## S3 method for class 'gamm'
simulate(
  object,
  nsim = 1,
  seed = NULL,
  data = newdata,
  weights = NULL,
  ...,
  newdata = NULL
)

## S3 method for class 'scam'
simulate(
  object,
  nsim = 1,
  seed = NULL,
  data = newdata,
  weights = NULL,
  ...,
  newdata = NULL
)

Arguments

object	a fitted GAM, typically the result of a call to mgcv::gam' or mgcv::gamm().
nsim	numeric; the number of posterior simulations to return.
seed	numeric; a random seed for the simulations.
data	data frame; new observations at which the posterior draws from the model should be evaluated. If not supplied, the data used to fit the model will be used for newdata, if available in object.
weights	numeric; a vector of prior weights. If newdata is null then defaults to object[["prior.weights"]], otherwise a vector of ones.
...	arguments passed to methods. simulate.gam() and simulate.scam() pass ... on to predict.gam(). As such you can pass additional arguments such as terms, exclude, to select which model terms are included in the predictions. This may be useful, for example, for excluding the effects of random effect terms.
newdata	Deprecated. Use data instead.

Details

For simulate.gam() to function, the family component of the fitted model must contain, or be updateable to contain, the required random number generator. See mgcv::fix.family.rd().

Value

(Currently) A data frame with nsim columns.

Author(s)

Gavin L. Simpson

Examples

load_mgcv()
dat <- data_sim("eg1", n = 400, dist = "normal", scale = 2, seed = 2)
m1 <- gam(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = dat, method = "REML")

sims <- simulate(m1, nsim = 5, seed = 42)
head(sims)

gavinsimpson/gratia documentation built on March 5, 2025, 10:01 a.m.