Skip to contents

Variance components by exact dense REML

Source: R/reml.R
reml_exact.Rd

Fits the same model as reml_sketch() with the same average-information updates, but forms and factorizes \(V\) and computes every trace exactly. It is meant for checking reml_sketch() on problems small enough to factorize.

Usage

reml_exact(y, G, X = NULL, start = NULL, tol = 1e-08, maxit = 100L)

Arguments

y

Numeric response.

G

A positive-semidefinite relationship matrix, or a lazy matrix from grm_matrix() or kernel_matrix(), which is formed in full.

X

Fixed-effect design matrix. Defaults to an intercept.

start

Starting values c(genetic, residual). Defaults to half the residual variance of a least-squares fit for each.

tol

Stop when no variance component changes by more than this fraction between iterations.

maxit

Maximum number of REML iterations.

Value

An object of class reml_sketch whose approx is "exact".

References

Gilmour, A. R., Thompson, R. & Cullis, B. R. (1995) Average information REML: an efficient algorithm for variance parameter estimation in linear mixed models. Biometrics 51, 1440-1450. doi:10.2307/2533274

See also

reml_sketch()

Examples

set.seed(1)
dat <- sim_genomic(n = 300, p = 600, h2 = 0.5)
reml_exact(dat$y, dat$G)
#> <reml_sketch> converged in 8 iterations (exact dense fit)
#>          estimate std.error
#> genetic    0.3934    0.1231
#> residual   0.6216    0.1098
#> h2         0.3876    0.1088