vcm.lm {asreml}R Documentation

Specify constraints among variance components

Description

Construct a constraints matrix that specifies linear constraints among variance components.

Usage

vcm.lm(
  form,
  data,
  drop.unused.levels = TRUE,
  intercept = FALSE,
  na.action = na.fail
)

Arguments

form

A model formula including at least one factor with up to n_c levels, where n_c is the number of variance parameters to be considered in the constrained set.

data

A data frame with a factor Vparameter, whose levels are taken from the full set of variance parameters, in which to resolve the names in form.

drop.unused.levels

If TRUE, unused levels in factors are removed (default = TRUE).

intercept

if FALSE, the intercept is not included in the call to model.matrix when forming the constraints matrix (default = FALSE).

na.action

The default, na.fail, is to terminate abnormally if missing values are present.

Details

Variance parameter constraints are specified through a design matrix F from a simple linear model. Let \kappa be the r-vector of original variance parameters (for either the sigma or gamma parameterisation) from which we wish to specify linear relationships of the form \kappa = F \kappa_n, where \kappa_n is the c-vector of parameters in the new set. In the simple, case where the r parameters are constrained to be equal c = 1, the r original parameters are all equal to the one new parameter and F will contain a column of ones.

The matrix F is given as the value to the vcm argument of asreml. F must have a dimnames attribute with the names of \kappa as its row names.

A data frame containing a factor Vparameter, whose levels are the r names of the variance parameters is returned by asreml when start.values = TRUE. The matrix F is obtained from a call to model.matrix using form and additional factors derived from or interacting with Vparameter.

Value

An r \times c matrix F specifying the variance parameter constraints where c is the length of the reduced vector of variance parameters. In a simple case with r parameters and the r-1 and r parameters are constrained to be equal, then c = r-1 and the j^{th} (1 = j < c) column of F has 1 in the j^{th} row and zero elsewhere; the c^{th} column has 1 in the c = (r-1) and r rows and zero elsewhere.

Examples


# Suppose there are four variance parameters: g1, g2, g3, and g4,
# and we wish to constrain g2 & g3 to be equal (note these are in
# positions 2 and 3).

# Generate gg as though from asreml(..., start.values = TRUE)

gg <- data.frame(Vparameter = c("g1", "g2", "g3", "g4"),
                        fac = factor(c(1, 2, 2, 3)))
F <- vcm.lm(~fac, data = gg)
# F
#    fac1 fac2 fac3
# g1    1    0    0
# g2    0    1    0
# g3    0    1    0
# g4    0    0    1
[Package asreml version 4.2.0.480 Index]