uncm

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

<code>uncm</code> creates a square matrix with 2's in the diagnals and off-diagonals to quickly specify an unconstrained constraint in the Gtc argument of the <code><a rd-options="" href="/link/vs?package=sommer&version=3.8" data-mini-rdoc="sommer::vs">vs</a></code> function.

Structural multivariate-univariate linear mixed model solver for multiple random effects and estimation of 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>). ML/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) to include multiple known relationship matrices and estimate complex unknown covariance structures. Spatial models can be fitted using the two-dimensional spline functionality in sommer.

Giovanny Covarrubias-Pazaran

sommer

Solving Mixed Model Equations in R

uncm function

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

uncm: unconstrained indication matrix

Description

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See Also

Examples