coda_replacement: Replacement of missing values and below-detection zeros in...

In coda.base: A Basic Set of Functions for Compositional Data Analysis

Replacement of missing values and below-detection zeros in compositional data

Description

Performs imputation of missing values and/or values below the detection limit in compositional data using an EM algorithm assuming normality on the simplex.

Usage

coda_replacement(
  X,
  DL = NULL,
  dl_prop = 0.65,
  eps = 1e-04,
  parameters = FALSE,
  debug = FALSE,
  maxit = 500
)

Arguments

X	A compositional data set: numeric matrix or data frame where rows represent observations and columns represent parts.
DL	An optional matrix or vector of detection limits. If 'NULL', the minimum non-zero value in each column of 'X' is used.
dl_prop	A numeric value between 0 and 1 used for initialization in the EM algorithm.
eps	Convergence tolerance.
parameters	Logical; if 'TRUE', return additional estimated parameters.
debug	Logical; if 'TRUE', print the log-likelihood at each iteration.
maxit	Maximum number of iterations

Value

If 'parameters = FALSE', a numeric matrix with imputed values. If 'parameters = TRUE', a list with the estimated clr mean, clr covariance, and imputed clr coordinates.

coda.base documentation built on March 4, 2026, 9:06 a.m.