fit_nonstationary_MRA: Title

In jtipton25/sgMRA: Multi-Resolution Gaussian Process Approximations with Stochastic Gradient Descent

Title

Description

Title

Usage

fit_nonstationary_MRA(
  y,
  locs,
  grid,
  grid_kernels,
  radius = 0.5,
  trunc = 0.01,
  alpha = NULL,
  alpha_a = NULL,
  alpha_b = NULL,
  learn_rate = 0.001,
  rate_schedule = NULL,
  n_iter = 500,
  n_message = 50,
  plot_during_fit = FALSE,
  adam_pars = NULL
)

Arguments

y	The data
locs	An N x 2 matrix of spatial locations
grid	A grid object
grid_kernels	A grid object for the spatially-varying kernels
trunc	The truncation parameter for the kernel parameters
alpha	If specified, the top layer MRA parameters
alpha_a	If specified, the parameters for the x co-ordinate of the kernels
alpha_b	If specified, the parameters for the y co-ordinate of the kernels
learn_rate	The gradient descent learning rate
rate_schedule	If specified, the gradient descent learning rate schedule in decreasing values.
n_iter	The number of gradient descent iterations
n_message	The number of iterations between which to output a message
plot_during_fit	Plot the current parameter states every n_message iterations
adam_pars	The adam parameter state to allow restarting the model

jtipton25/sgMRA documentation built on Feb. 9, 2023, 4:53 a.m.