fit: Generic 'fit' method for a 'GPModel'

Description Usage Arguments Author(s)

View source: R/GPModel.R

Description

Generic 'fit' method for a GPModel

Usage

1
fit(gp_model, y, X, params, fixed_effects = NULL)

Arguments

gp_model

a GPModel

y

A vector with response variable data

X

A matrix with covariate data for fixed effects ( = linear regression term)

params

A list with parameters for the model fitting / optimization

  • optimizer_cov Optimizer used for estimating covariance parameters. Options: "gradient_descent", "fisher_scoring", and "nelder_mead". Default = "gradient_descent"

  • optimizer_coef Optimizer used for estimating linear regression coefficients, if there are any (for the GPBoost algorithm there are usually none). Options: "gradient_descent", "wls", and "nelder_mead". Gradient descent steps are done simultaneously with gradient descent steps for the covariance parameters. "wls" refers to doing coordinate descent for the regression coefficients using weighted least squares. Default="wls" for Gaussian data and "gradient_descent" for other likelihoods.

  • maxit Maximal number of iterations for optimization algorithm. Default=1000.

  • delta_rel_conv Convergence criterion: stop optimization if relative change in parameters is below this value. Default=1E-6.

  • init_coef Initial values for the regression coefficients (if there are any, can be NULL). Default=NULL.

  • init_cov_pars Initial values for covariance parameters of Gaussian process and random effects (can be NULL). Default=NULL.

  • lr_coef Learning rate for fixed effect regression coefficients if gradient descent is used. Default=0.1.

  • lr_cov Learning rate for covariance parameters. If <= 0, internal default values are used. Default value = 0.1 for "gradient_descent" and 1. for "fisher_scoring"

  • use_nesterov_acc If TRUE Nesterov acceleration is used. This is used only for gradient descent. Default=TRUE

  • acc_rate_coef Acceleration rate for regression coefficients (if there are any) for Nesterov acceleration. Default=0.5.

  • acc_rate_cov Acceleration rate for covariance parameters for Nesterov acceleration. Default=0.5.

  • momentum_offset Number of iterations for which no mometum is applied in the beginning. Default=2.

  • trace If TRUE, information on the progress of the parameter optimization is printed. Default=FALSE.

  • convergence_criterion The convergence criterion used for terminating the optimization algorithm. Options: "relative_change_in_log_likelihood" (default) or "relative_change_in_parameters".

  • std_dev If TRUE, (asymptotic) standard deviations are calculated for the covariance parameters

fixed_effects

A vector of optional external fixed effects which are held fixed during training.

Author(s)

Fabio Sigrist


gpboost documentation built on July 14, 2021, 9:06 a.m.