unsm

integer specifying the number of traits to be fitted for a given random effect.

integer specifying the number of times the matrix should be repeated in a list format to provide easily the constraints in complex models that use the ds(), us() or cs() structures.

reps

<code>unsm</code> creates a square matrix with ones in the diagonals and 2's in the off-diagonals to quickly specify an unstructured constraint in the Gtc argument of the <code><a rd-options="" href="/link/vs?package=sommer&version=4.1.4" data-mini-rdoc="sommer::vs">vs</a></code> function.

Structural multivariate-univariate linear mixed model solver for estimation of multiple random effects and unknown variance-covariance structures (i.e. heterogeneous and unstructured variance models) (Covarrubias-Pazaran, 2016 <doi:10.1371/journal.pone.0156744>; Maier et al., 2015 <doi:10.1016/j.ajhg.2014.12.006>). REML estimates can be obtained using the Direct-Inversion Newton-Raphson and Direct-Inversion Average Information algorithms. Designed for genomic prediction and genome wide association studies (GWAS), particularly focused in the p > n problem (more coefficients than observations) and dense known covariance structures for levels of random effects. Spatial models can also be fitted using the two-dimensional spline functionality available in sommer.

Giovanny Covarrubias-Pazaran

sommer

Solving Mixed Model Equations in R

unsm function

<code>unsm</code> creates a square matrix with ones in the diagonals and 2's in the off-diagonals to quickly specify an unstructured constraint in the Gtc argument of the <code><a rd-options='' href='vs'>vs</a></code> function.

unsm: unstructured indication matrix

Description

Usage

Arguments

Value

References

See Also

Examples