AIREMLF90
A modification of REMLF90 with computing by the Average-Information
Algorithm.
Written by Shogo Tsuruta, University of Georgia, 03/99-07/99
AIREMLF90 uses a second derivative REML algrithm with extra heuristics, as is
described in Jensen et al. (1996-7). For most problems, it converges in far
fewer rounds than EM REML as implemented in REMLF90. While typically REMLF90
takes 50-300 rounds to converge, AIREMLF90 converges in 5-15 rounds and to a
higher accuracy. For selected problems, AI REML fails to converge when the
covariance matrix is close to non-positive definite. Adjust sensitivity of the
program by setting the appropriate tolerance.
Several options are avaiable:
OPTION conv_crit 1d-12
convergence criterion (default 1d-10).
OPTION maxrounds 500
maximum rounds (default 5000).
when it is negative, the program calculates BLUP without running REML.
OPTION EM-REML 10
run EM-REML for first 10 rounds to get initial variances within the
parameter space (default 0).
OPTION tol 1d-12
tolerance (or precision) (default 1d-14) for positive definite matrix and
g-inverse subroutines.
OPTION sol se
store solutions and s.e.
OPTION residual
y-hat and residual will be shown in yhat_residual.
OPTION missing -1
set the missing observation (default 0).
OPTION constant_var 5 1 2
The effect number (5), the first trait number (1), and the second trait number (2), implying the covariance between traits 1 and 2 for effect 5.
# Heterogeneous residual variances for a single trait
OPTION hetres_pos 10 11
specify the position of covariables.
OPTION hetres_pol 4.0 0.1 0.1
initial values of coefficients for heterogeneous residual variances
use ln(a0, a1, a2, ...) to make these values.
# Heterogeneous residual variances for mutiple traits
OPTION hetres_pos 10 10 11 11
specify the position of covariables (trait first).
OPTION hetres_pol 4.0 4.0 0.1 0.1 0.01 0.01
initial values of coefficients for heterogeneous residual variances
use ln(a0, a1, a2, ...) to make these values (trait first).