predict.evinb {evinf}

Predictions from evinb object

Description

Predictions from evinb object

Usage

## S3 method for class 'evinb'
predict(
  object,
  newdata = NULL,
  type = c("harmonic", "explog", "counts", "pareto_alpha", "evinf", "count_state",
    "states", "all", "quantile"),
  pred = c("original", "bootstrap_median", "bootstrap_mean"),
  quantile = NULL,
  confint = FALSE,
  conf_level = 0.9,
  multicore = FALSE,
  ncores = NULL,
  ...
)

Arguments

object

An evinb object for which to produce predicted values

newdata

Optional new data (tibble) to produce predicted values from

type

Character string, 'harmonic' for the harmonic mean and 'explog' for exponentiated expected log, 'counts' for predicted count of the negative binomial component, 'pareto_alpha' for the predicted pareto alpha value, 'states' for the predicted component states (prior), 'count_state' for predicted probability of the count state, 'evinf' for predicted probability of the pareto state, 'all' for all predicted values, and 'quantile' for quantile prediction.

pred

Type of prediction to be used, defaults to the original prediction from the fitted model, with alternatives being the bootstrapped median or mean. Note that bootstrap mean may yield infinite values, especially when doing quantile prediction

quantile

Quantile for which to produce quantile prediction

confint

Should confidence intervals be made for the predictions? Note: only available for vector type predictions and not 'states' and 'all'.

conf_level

What confidence level should be used for confidence intervals

multicore

Should multicore be used when calculating quantile prediction? Often it is enough to run quantile prediction on a single core, but in cases of large data or very skewed distributions it may be useful to run multicore

ncores

Number of cores to be used for multicore.

...

Other arguments passed to predict function

Value

A vector of predicted values for type 'harmonic', 'explog', 'counts', 'pareto_alpha','evinf', 'count_state', and 'quantile' or a tibble of predicted values for type 'states' and 'all' or if confint=T

Examples

data(genevzinb2)
model <- evinb(y~x1+x2+x3,data=genevzinb2, n_bootstraps = 10)
predict(model)
predict(model, type='all') # Getting all of the available predicted values