validate_lmm_input: Validate Inputs for Catalytic Linear Mixed Model (LMM)

In catalytic: Tools for Applying Catalytic Priors in Statistical Modeling

Validate Inputs for Catalytic Linear Mixed Model (LMM)

Description

This function validates the parameters needed for fitting a catalytic Linear Mixed Model (LMM) or Generalized Linear Model (GLM), specifically for the use with the categorical initialization from cat_lmm_initialization.

Usage

validate_lmm_input(
  cat_init,
  tau = NULL,
  residual_variance_0 = NULL,
  random_effect_variance_0 = NULL,
  coefs_0 = NULL,
  optimize_domain = NULL,
  max_iter = NULL,
  tol = NULL,
  tau_seq = NULL,
  cross_validation_fold_num = NULL
)

Arguments

cat_init	An object of class cat_initialization, typically generated from the cat_lmm_initialization function.
tau	A positive numeric value specifying the penalty parameter for the model.
residual_variance_0	A positive numeric value for the initial residual variance estimate.
random_effect_variance_0	A positive numeric value for the initial random effect variance estimate.
coefs_0	A numeric vector of length equal to the number of columns in the observation matrix. This represents the initial values for the model coefficients.
optimize_domain	A numeric vector of length 2 specifying the domain for the optimization procedure.
max_iter	A positive integer specifying the maximum number of iterations for the optimization.
tol	A positive numeric value indicating the tolerance level for convergence.
tau_seq	A numeric vector representing a sequence of values for the penalty parameter.
cross_validation_fold_num	A positive integer specifying the number of folds for cross-validation.

Details

This function performs the following checks:

• Ensures that tau, tau_seq, residual_variance_0, random_effect_variance_0, optimize_domain, max_iter, and tol are positive values.

• Verifies that cat_init is an object generated by cat_lmm_initialization.

• Checks if coefs_0 has the same length as the number of columns in the observation matrix of cat_init.

• Ensures optimize_domain is a numeric vector of length 2.

• Confirms that cross_validation_fold_num is greater than 1 and less than the number of observations in cat_init. If any of these conditions are not met, the function raises an error to guide the user.

Value

Returns nothing if all checks pass; otherwise, raises an error.

catalytic documentation built on April 4, 2025, 5:51 a.m.