Predict counts of a new sample

Usage

# S3 method for class 'ZIPLNfit'
predict(
  object,
  newdata,
  responses = NULL,
  level = 1,
  type = c("link", "response", "deflated"),
  ...
)

Arguments

object: an R6 object with class ZIPLNfit
newdata: A data frame in which to look for variables and offsets with which to predict
responses: Optional data frame containing the count of the observed variables (matching the names of the provided as data in the PLN function), assuming the interest in in testing the model.
level: Optional integer value the level to be used in obtaining the predictions. Level zero corresponds to the population predictions (default if responses is not provided) while level one (default) corresponds to predictions after evaluating the variational parameters for the new data.
type: Scale used for the prediction. Either "link" (default, predicted positions in the latent space), "response" (predicted average counts, accounting for zero-inflation) or "deflated" (predicted average counts, not accounting for zero-inflation and using only the PLN part of the model).
...: additional parameters for S3 compatibility. Not used

Value

A matrix of predicted log-counts (if type = "link") or predicted counts, accounting for zero-inflation (if type = "response") or not (if type = "deflated").

Details

Note that level = 1 can only be used if responses are provided, as the variational parameters can't be estimated otherwise. In the absence of responses, level is ignored and the fitted values are returned

Note also that when type = "response" corresponds to predicting values with \((1 - \pi)A\), where \(A\) is the average count in the PLN part of the model and \(\pi\) the probability of zero-inflation, whereas type = "deflated" corresponds to \(A\).