graphld.blup

Best Linear Unbiased Prediction (BLUP) for effect size estimation.

Under the infinitesimal model with per-s.d. effect sizes $\beta \sim N(0, D)$, the BLUP effect sizes are:

$E(\beta) = \sqrt{n} D (nD + R^{-1})^{-1} R^{-1}z$

where $R^{-1}$ is approximated with the LDGM precision matrix. Public BLUP workflows take heritability for the analyzed variant scope and set $\mathrm{trace}(D)$ equal to that value across matched LDGM effect indices.

For usage examples, see the BLUP guide.

::: graphld.blup options: show_root_heading: true members_order: source