## Response Probabilities for Negative Binomial Models

### Description

This is the method add_probs uses if the model fit is an object of class negbin. Probabilities are determined through simulation, using the same method as add_pi.negbin.

### Usage

## S3 method for class 'negbin'
df,
fit,
q,
name = NULL,
yhatName = "pred",
comparison = "<",
nSims = 2000,
...
)


### Arguments

 df A data frame of new data. fit An object of class negbin. Predictions are made with this object. q A double. A quantile of the response distribution. name NULL or a string. If NULL, probabilities automatically will be named by add_probs(), otherwise, the probabilities will be named name in the returned data frame. yhatName A string. Name of the vector of predictions. comparison A character vector of length one. Permitted arguments are "=", "<", "<=", ">", or ">=". The default value is "<". nSims A positive integer. Controls the number of simulated draws. ... Additional arguments.

### Value

A dataframe, df, with predicted values and probabilities attached.

add_ci.negbin for confidence intervals for negbin objects, add_pi.negbin for prediction intervals of negbin objects, and add_quantile.negbin for response quantiles of negbin objects.

### Examples

x1 <- rnorm(100, mean = 1)
y <- MASS::rnegbin(n = 100, mu = exp(1 + x1), theta = 5)
df <- data.frame(x1 = x1, y = y)
fit <- MASS::glm.nb(y ~ x1, data = df)