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Fit a logistic Gaussian process in R for a binary outcome

logistic_gaussian_process.Rd

Fit a logistic Gaussian process in R for a binary outcome

Usage

logistic_gaussian_process(
  formula,
  data,
  sparse = T,
  n_points = 10,
  n_particles = 10,
  n_iter = 2000
)

Arguments

data

the dataframe from which to source regression data.

sparse

a Boolean indicating whether to use the projected process approximation to speed up training. Recommended for N>100.

n_points

The number of inducing points used for the projected process approximation. Defaults to 5. If set too large, may cause numerical stability issues when calculating the gradient of the marginal likelihood.

n_particles

number of particles to be used in the stein variational gradient descent simulation

form

the regression formula for the Gaussian process. The left-hand-side gives determines outcome you are fitting the GP to, and the right-hand side gives the kernel specification.