NEWS.md
variance_jackknife()
and variance_bootstrap()
to prevent estimation recycling, results from those functions are now comparable to doing jackknife / bootstrap “by hand”.predict()
function for PLNfit model to (i) return fitted values if newdata is missing or (ii) perform one VE step to improve fit if responses are provided (fix issue #114)scale
argument compute_offset() to force the offsets (RLE, CSS, GMPR, Wrench) to be on the same scale as the counts, like TSS.clusters
) is not of the form 1:K_max
PLNLDA()
and changing extract_model()
to conform with model.frame()
$VEStep()
for PLN-PCA, dealing with low rank matrices$project()
for PLN-PCA, used to project newdata into PCA space$latent_pos()
which is equivalent to active binding $latent