OpenMxModel {sharp}

Writing OpenMx model (matrix specification)

Description

Returns matrix specification for use in mxModel from (i) the adjacency matrix of a Directed Acyclic Graph (asymmetric matrix A in Reticular Action Model notation), and (ii) a binary matrix encoding nonzero entries in the residual covariance matrix (symmetric matrix S in Reticular Action Model notation).

Usage

OpenMxModel(adjacency, residual_covariance = NULL, manifest = NULL)

Arguments

adjacency

binary adjacency matrix of the Directed Acyclic Graph (transpose of the asymmetric matrix A in Reticular Action Model notation). The row and column names of this matrix must be defined.

residual_covariance

binary and symmetric matrix encoding the nonzero entries in the residual covariance matrix (symmetric matrix S in Reticular Action Model notation). By default, this is the identity matrix (no residual covariance).

manifest

optional vector of manifest variable names.

Value

A list of RAM matrices that can be used in mxRun.

See Also

PenalisedOpenMx, OpenMxMatrix

Examples

if (requireNamespace("OpenMx", quietly = TRUE)) {
  # Definition of simulated effects
  pk <- c(3, 2, 3)
  dag <- LayeredDAG(layers = pk)
  theta <- dag
  theta[2, 4] <- 0
  theta[3, 7] <- 0
  theta[4, 7] <- 0

  # Data simulation
  set.seed(1)
  simul <- SimulateStructural(n = 500, v_between = 1, theta = theta, pk = pk)

  # Writing RAM matrices for mxModel
  ram_matrices <- OpenMxModel(adjacency = dag)

  # Running unpenalised model
  unpenalised <- OpenMx::mxRun(OpenMx::mxModel(
    "Model",
    OpenMx::mxData(simul$data, type = "raw"),
    ram_matrices$Amat,
    ram_matrices$Smat,
    ram_matrices$Fmat,
    ram_matrices$Mmat,
    OpenMx::mxExpectationRAM("A", "S", "F", "M", dimnames = colnames(dag)),
    OpenMx::mxFitFunctionML()
  ), silent = TRUE, suppressWarnings = TRUE)
  unpenalised$A$values

  # Incorporating latent variables
  ram_matrices <- OpenMxModel(
    adjacency = dag,
    manifest = paste0("x", seq_len(7))
  )
  ram_matrices$Fmat$values

  # Running unpenalised model
  unpenalised <- OpenMx::mxRun(OpenMx::mxModel(
    "Model",
    OpenMx::mxData(simul$data[, seq_len(7)], type = "raw"),
    ram_matrices$Amat,
    ram_matrices$Smat,
    ram_matrices$Fmat,
    ram_matrices$Mmat,
    OpenMx::mxExpectationRAM("A", "S", "F", "M", dimnames = colnames(dag)),
    OpenMx::mxFitFunctionML()
  ), silent = TRUE, suppressWarnings = TRUE)
  unpenalised$A$values
}