Build TMB Fit Result List

This helper does some simple post-processing of the TMB object and optimization results, including setting names, inverting matrices etc.

Usage

h_mmrm_tmb_fit(tmb_object, tmb_opt, formula_parts, tmb_data)

Arguments

tmb_object

(list)
created with TMB::MakeADFun().

tmb_opt

(list)
optimization result.

formula_parts

(mmrm_tmb_formula_parts)
produced by h_mmrm_tmb_formula_parts().

tmb_data

(mmrm_tmb_data)
produced by h_mmrm_tmb_data().

data

(data.frame)
input data containing the variables used in formula.

weights

(vector)
weights to be used in the fitting process.

Value

List of class mmrm_tmb with:

• cov: estimated covariance matrix, or named list of estimated group specific covariance matrices.

• beta_est: vector of coefficient estimates.

• beta_vcov: Variance-covariance matrix for coefficient estimates.

• beta_vcov_inv_L: Lower triangular matrix L of the inverse variance-covariance matrix decomposition.

• beta_vcov_inv_D: vector of diagonal matrix D of the inverse variance-covariance matrix decomposition.

• theta_est: vector of variance parameter estimates.

• theta_vcov: variance-covariance matrix for variance parameter estimates.

• neg_log_lik: obtained negative log-likelihood.

• formula_parts: input.

• data: input.

• weights: input.

• reml: input as a flag.

• opt_details: list with optimization details including convergence code.

• tmb_object: original TMB object created with TMB::MakeADFun().

• tmb_data: input.

Details

Instead of inverting or decomposing beta_vcov, it can be more efficient to use its robust Cholesky decomposition LDL^T, therefore we return the corresponding two components L and D as well since they have been available on the C++ side already.