inst/md/GBLUP.md

In gdlc/BGLR-R: Bayesian Generalized Linear Regression

Various Ways of fitting a 'GBLUP' model using BGLR

In the following example we show how to fit a GBLUP model (i.e., a Gaussian process) using different parameterization.

* [Using oringial inputs (e.g., SNPs)](#BRR) * [Using a G-matrix (or kernel)](#RKHS) * [Using eigenvalues and eigenvectors](#RKHS2) * [Using scaled-principal components)](#PC) * [Using a Cholesky decomposition](#CHOL) * [Using a QR decomposition](#QR)

--------------------------------------------- **(i) Providing the markers, using `model='BRR'`** In this case BGLR asigns iid normal priors to the marker effects. wzxhzdk:0 [Menu](#menu) ---------------------------------------------

**(2) Providing the G-matrix** BGLR Fits these Gaussian models using the eigenvalue decomposition og G. The eigenvalue decomposition is computed internally using `eigen()`. wzxhzdk:1 [Menu](#menu)

--------------------------------------------- **(3) Providing eigenvalues and eigenvectors** This strategy can be used to avoid computing the eigen-decomposition internally. This can be useful if a model will be fitted several times (e.g., cross-validation). wzxhzdk:2 [Menu](#menu)

--------------------------------------------- **(4) Providing scaled-eigenvectors and using `model='BRR'`** wzxhzdk:3 [Menu](#menu)

--------------------------------------------- **(5) Using the Cholesky decompositon and `model='BRR'`** This approach won't work if G is not positive definite; in our case the matrix is positive semi-definite, we can make it positive definite by adding a small constant to the diagonal. wzxhzdk:4 [Menu](#menu)

--------------------------------------------- **(6)Using QR-factorization** wzxhzdk:5 [Menu](#menu) [Back to examples](https://github.com/gdlc/BGLR-R/blob/master/README.md)

gdlc/BGLR-R documentation built on April 23, 2024, 11:01 p.m.