fido (version 1.0.4)

predict.pibblefit: Predict response from new data

Description

Predict response from new data

Usage

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

Value

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

Arguments

object

An object of class pibblefit

newdata

An optional matrix for which to evaluate predictions. If NULL (default), the original data of the model is used.

response

Options = "LambdaX":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$Y. Otherwise uses median colsums of m$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

Details

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

Examples

sim <- pibble_sim()
fit <- pibble(sim$Y, sim$X)
predict(fit)[,,1:2] # just show 2 samples