fitComponentModel Fit the estimated variance components of a model to covariance data

Usage

fitComponentModel(covmat, ...)

Arguments

covmat: The covariance matrix of the raw data, which may be blockwise.
...: Comma-separated relatedness component matrices representing the variance components of the model.

Value

A regression (linear model fitted with lm). The coefficients of the regression represent the estimated variance components.

Details

This function fits the estimated variance components of a model to given covariance data. The rank of the component matrices is checked to ensure that the variance components are all identified. Warnings are issued if there are inconsistencies.

Examples

if (FALSE) { # \dontrun{
# install.packages("OpenMX")
data(twinData, package = "OpenMx")
sellVars <- c("ht1", "ht2")
mzData <- subset(twinData, zyg %in% c(1), c(selVars, "zyg"))
dzData <- subset(twinData, zyg %in% c(3), c(selVars, "zyg"))

fitComponentModel(
  covmat = list(cov(mzData[, selVars], use = "pair"), cov(dzData[, selVars], use = "pair")),
  A = list(matrix(1, nrow = 2, ncol = 2), matrix(c(1, 0.5, 0.5, 1), nrow = 2, ncol = 2)),
  C = list(matrix(1, nrow = 2, ncol = 2), matrix(1, nrow = 2, ncol = 2)),
  E = list(diag(1, nrow = 2), diag(1, nrow = 2))
)
} # }