Predict counts of a new sample
an R6 object with class ZIPLNfit
A data frame in which to look for variables and offsets with which to predict
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.
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.
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
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 \(A\).