fitted_samples: Draw fitted values from the posterior distribution

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

Draw fitted values from the posterior distribution

Description

Expectations (fitted values) of the response drawn from the posterior distribution of fitted model using a Gaussian approximation to the posterior.

Usage

fitted_samples(model, ...)

## S3 method for class 'gam'
fitted_samples(
  model,
  n = 1,
  data = newdata,
  seed,
  scale = c("response", "linear_predictor"),
  method = c("gaussian", "mh", "inla"),
  freq = FALSE,
  unconditional = FALSE,
  ncores = 1L,
  ...,
  newdata = NULL
)

Arguments

model	a fitted model of the supported types
...	arguments passed to other methods. For fitted_samples(), these are passed on to predict.gam().
n	numeric; the number of posterior samples to return.
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 data, if available in model.
seed	numeric; a random seed for the simulations.
scale	character;
method	character; the method used to generate samples from the posterior distribution of the model. "gaussian", the default, uses a Gaussian approximation to the posterior. "mh" uses a simple Metropolis Hastings sampler, while "inla" uses a variant of Integrated Nested Laplace Approximation due to Wood (2019). Currently, the only available option is "gaussian".
freq	logical; TRUE to use the frequentist covariance matrix of the parameter estimators, FALSE to use the Bayesian posterior covariance matrix of the parameters.
unconditional	logical; if TRUE (and freq == FALSE) then the Bayesian smoothing parameter uncertainty corrected covariance matrix is used, if available.
ncores	number of cores for generating random variables from a multivariate normal distribution. Passed to mvnfast::rmvn(). Parallelization will take place only if OpenMP is supported (but appears to work on Windows with current R).
newdata	Deprecated: use data instead.

Value

A tibble (data frame) with 3 columns containing the posterior predicted values in long format. The columns are

• row (integer) the row of data that each posterior draw relates to,

• draw (integer) an index, in range 1:n, indicating which draw each row relates to,

• response (numeric) the predicted response for the indicated row of data.

Author(s)

Gavin L. Simpson

References

Wood, S.N., (2020). Simplified integrated nested Laplace approximation. Biometrika 107, 223–230. doi: 10.1093/biomet/asz044

Examples

load_mgcv()

dat <- data_sim("eg1", n = 1000, dist = "normal", scale = 2, seed = 2)
m1 <- gam(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = dat, method = "REML")

fs <- fitted_samples(m1, n = 5, seed = 42)

fs

gratia documentation built on Feb. 16, 2023, 10:40 p.m.