Predict using basset

# S3 method for bassetfit
predict(
  object,
  newdata,
  response = "Lambda",
  size = NULL,
  use_names = TRUE,
  summary = FALSE,
  iter = NULL,
  from_scratch = FALSE,
  ...
)

Arguments

object: An object of class pibblefit
newdata: An optional matrix for which to evaluate prediction.
response: Options = "Lambda":Mean of regression, "Eta", "Y": counts
size: the number of counts per sample if response="Y" (as vector or matrix), default if newdata=NULL and response="Y" is to use colsums of m$Y. Otherwise uses median colsums of object$Y as default. If passed as a matrix should have dimensions ncol(newdata) x iter.
use_names: if TRUE apply names to output
summary: if TRUE, posterior summary of predictions are returned rather than samples
iter: number of iterations to return if NULL uses object$iter
from_scratch: should predictions of Y come from fitted Eta or from predictions of Eta from posterior of Lambda? (default: false)
...: other arguments passed to summarise_posterior

Value

(if summary==FALSE) array D x N x iter; (if summary==TRUE) tibble with calculated posterior summaries

Details

currently only implemented for pibblefit objects in coord_system "default" "alr", or "ilr".