quantile.HurdleNegativeBinomial {distributions3} R Documentation

## Determine quantiles of a hurdle negative binomial distribution

### Description

quantile() is the inverse of cdf().

### Usage

## S3 method for class 'HurdleNegativeBinomial'
quantile(x, probs, drop = TRUE, elementwise = NULL, ...)


### Arguments

 x A HurdleNegativeBinomial object created by a call to HurdleNegativeBinomial(). probs A vector of probabilities. drop logical. Should the result be simplified to a vector if possible? elementwise logical. Should each distribution in x be evaluated at all elements of probs (elementwise = FALSE, yielding a matrix)? Or, if x and probs have the same length, should the evaluation be done element by element (elementwise = TRUE, yielding a vector)? The default of NULL means that elementwise = TRUE is used if the lengths match and otherwise elementwise = FALSE is used. ... Arguments to be passed to qhnbinom. Unevaluated arguments will generate a warning to catch mispellings or other possible errors.

### Value

In case of a single distribution object, either a numeric vector of length probs (if drop = TRUE, default) or a matrix with length(probs) columns (if drop = FALSE). In case of a vectorized distribution object, a matrix with length(probs) columns containing all possible combinations.

### Examples

## set up a hurdle negative binomial distribution
X <- HurdleNegativeBinomial(mu = 2.5, theta = 1, pi = 0.75)
X

## standard functions
pdf(X, 0:8)
cdf(X, 0:8)
quantile(X, seq(0, 1, by = 0.25))

## cdf() and quantile() are inverses for each other
quantile(X, cdf(X, 3))

## density visualization
plot(0:8, pdf(X, 0:8), type = "h", lwd = 2)

## corresponding sample with histogram of empirical frequencies
set.seed(0)
x <- random(X, 500)
hist(x, breaks = -1:max(x) + 0.5)


[Package distributions3 version 0.2.1 Index]