Description Usage Arguments Details Value See Also Examples
View source: R/add_pi_negbin.R
This function is one of the methods for add_pi, and is
called automatically when add_pi is used on a fit of
class negbin.
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df |
A data frame of new data. |
fit |
An object of class |
alpha |
A real number between 0 and 1. Controls the confidence level of the interval estimates. |
names |
|
yhatName |
A string. Name of the predictions vector. |
nSims |
A positive integer. Determines the number of simulations to run. |
... |
Additional arguments. |
Prediction intervals for negative binomial fits are formed through a two part simulation scheme:
1. Model coefficients are generated through a parametric bootstrap procedure that simulates the uncertainty in the regression coefficients.
2. Random draws from the negative binomial distribution are taken with a mean that varies based on the model coefficients determined in step (1) and over-dispersion parameter that is taken from the original fitted model.
Quantiles of the simulated responses are taken at the end to produce intervals of the desired level.
A dataframe, df, with predicted values, upper and lower
prediction bounds attached.
add_ci.negbin for confidence intervals for
negbin objects, add_probs.negbin for conditional
probabilities of negbin objects, and
add_quantile.negbin for response quantiles of
negbin objects.
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