Calculate the mean given parameters

Usage

meaninate(
  gammas,
  B,
  X,
  Z,
  P,
  X_tilde,
  Z_tilde = NULL,
  Z_tilde_gamma_cols,
  P_tilde,
  gamma_tilde,
  alpha_tilde = NULL,
  Z_tilde_list = NULL,
  return_separate = FALSE,
  exclude_gammas = FALSE
)

Arguments

gammas: A numeric vector of length n of starting values for read intensity parameter gamma
B: A \(p \times J\) numeric matrix giving initial values for the sample efficiencies.
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.
P: A \(K \times J\) numeric matrix giving initial values for the relative abundance matrix.
X_tilde: A \(\tilde{K} \times p\) matrix giving the spurious read source efficiency design matrix
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).
P_tilde: A \(\tilde{K} \times J\) numeric matrix giving initial values for the spurious read source relative abundances.
gamma_tilde: A numeric vector of length \(\tilde{K}\) of starting values for spurious read intensity parameter gamma_tilde
alpha_tilde: A numeric vector containing starting values of length \(M\). If used, Z_tilde_list must be provided.
Z_tilde_list: A list of length \(M + 1\) containing matrices \(\tilde{Z}_1,\dots,\tilde{Z}_{M + 1}\) to be linearly combined to generate Z_tilde: \(\tilde{Z} = \tilde{Z}_{(1)} + \sum_{m = 1}^M \exp(\tilde{\alpha}_m)\tilde{Z}_{(m + 1)}\). If used, alpha_tilde must be provided.
return_separate: Boolean. Return the summed mean, or separate the sample and contamination pieces. Defaults to FALSE.
exclude_gammas: Boolean, defaults to FALSE. Should the gamma components be ignored?