Criterion Evaluation Function

Evaluates the objective function used during model fitting under either a Poisson likelihood criterion or a GMM criterion.

Usage

evaluate_criterion_lr(
  W,
  X,
  Z,
  Z_tilde,
  Z_tilde_gamma_cols,
  Z_tilde_list = NULL,
  X_tilde,
  fixed_df,
  varying_df,
  varying_lr_df = NULL,
  barrier_t = NULL,
  criterion = "Poisson",
  lr_scale = TRUE,
  include_log_penalty = TRUE,
  wts = NULL,
  gmm_inv_wts = NULL,
  return_gmm_inv_weights = FALSE
)

Arguments

W

An \(n \times J\) matrix of numeric HTS output (e.g., read counts, coverages, etc.)

X

The sample efficiency design – an \(n \times p\) matrix

Z

The sample-specimen design – an \(n \times K\) matrix whose \(ij\)-th entry indicates the proportional contribution of specimen \(j\) to sample \(i\). Rows must sum to 1 or be identically 0.

Z_tilde

The spurious read design – an \(n \times \tilde{K}\) matrix where \(\tilde{K}\) is the number of spurious read sources modeled.

Z_tilde_gamma_cols

A numeric vector containing the columns of Z_tilde which should be multiplied by exp(gamma).

Z_tilde_list

Optional list-form representation of Z_tilde or related auxiliary structures.

X_tilde

Design matrix associated with spurious-read or auxiliary components of the mean model.

fixed_df

A data frame of fixed model parameters.

varying_df

A data frame of parameters currently being optimized, represented on the natural scale unless lr_scale = TRUE.

varying_lr_df

Optional data frame of varying parameters on the log-ratio scale. Used when lr_scale = TRUE.

barrier_t

Optional numeric tuning parameter for the log-ratio barrier penalty.

criterion

Character string specifying the criterion to evaluate. Currently one of "Poisson" or "GMM".

lr_scale

Logical; if TRUE, convert log-ratio scale parameters to relative abundance scale before evaluation.

include_log_penalty

Logical; if TRUE, include the log-barrier penalty when lr_scale = TRUE.

wts

Optional numeric weights

gmm_inv_wts

Optional inverse weighting matrix or vector for the GMM criterion. If NULL, it is estimated internally

return_gmm_inv_weights

Logical; if TRUE and criterion = "GMM", return both the GMM criterion value and the inverse weights.

Value

If criterion = "Poisson", a single numeric criterion value.

If criterion = "GMM" and return_gmm_inv_weights = FALSE, a single numeric criterion value.

If criterion = "GMM" and return_gmm_inv_weights = TRUE, a list with components:

gmm_crit

The numeric GMM criterion value.

inv_wts

The inverse weights used in the GMM calculation.