predict.PLNmixturefit: Prediction for a 'PLNmixturefit' object

In PLN-team/PLNmodels: Poisson Lognormal Models

Prediction for a PLNmixturefit object

Description

Predict either posterior probabilities for each group or latent positions based on new samples

Usage

## S3 method for class 'PLNmixturefit'
predict(
  object,
  newdata,
  type = c("posterior", "response", "position"),
  prior = matrix(rep(1/object$k, object$k), nrow(newdata), object$k, byrow = TRUE),
  control = PLNmixture_param(),
  ...
)

Arguments

object	an R6 object with class PLNmixturefit
newdata	A data frame in which to look for variables, offsets and counts with which to predict.
type	The type of prediction required. The default posterior are posterior probabilities for each group , response is the group with maximal posterior probability and latent is the averaged latent in the latent space, with weights equal to the posterior probabilities.
prior	User-specified prior group probabilities in the new data. The default uses a uniform prior.
control	a list-like structure for controlling the fit. See PLNmixture_param() for details.
...	additional parameters for S3 compatibility. Not used

Value

A matrix of posterior probabilities for each group (if type = "posterior"), a matrix of (average) position in the latent space (if type = "position") or a vector of predicted groups (if type = "response").

Examples

data(trichoptera)
trichoptera <- prepare_data(trichoptera$Abundance, trichoptera$Covariate)
myPLN <- PLNmixture(Abundance ~ 1 + offset(log(Offset)),
           data = trichoptera, control = PLNmixture_param(smoothing = "none"))  %>% getBestModel()
predict(myPLN, trichoptera, "posterior")
predict(myPLN, trichoptera, "position")
predict(myPLN, trichoptera, "response")

PLN-team/PLNmodels documentation built on April 15, 2024, 9:01 a.m.