# pdf: Evaluate the probability density of a probability... In distributions3: Probability Distributions as S3 Objects

 pdf R Documentation

## Evaluate the probability density of a probability distribution

### Description

Generic function for computing probability density function (PDF) contributions based on a distribution object and observed data.

### Usage

```pdf(d, x, drop = TRUE, ...)

log_pdf(d, x, ...)

pmf(d, x, ...)
```

### Arguments

 `d` An object. The package provides methods for distribution objects such as those from `Normal()` or `Binomial()` etc. `x` A vector of elements whose probabilities you would like to determine given the distribution `d`. `drop` logical. Should the result be simplified to a vector if possible? `...` Arguments passed to methods. Unevaluated arguments will generate a warning to catch mispellings or other possible errors.

### Details

The generic function `pdf()` computes the probability density, both for continuous and discrete distributions. `pmf()` (for the probability mass function) is an alias that just calls `pdf()` internally. For computing log-density contributions (e.g., to a log-likelihood) either `pdf(..., log = TRUE)` can be used or the generic function `log_pdf()`.

### Value

Probabilities corresponding to the vector `x`.

### Examples

```## distribution object
X <- Normal()
## probability density
pdf(X, c(1, 2, 3, 4, 5))
pmf(X, c(1, 2, 3, 4, 5))
## log-density
pdf(X, c(1, 2, 3, 4, 5), log = TRUE)
log_pdf(X, c(1, 2, 3, 4, 5))
```

distributions3 documentation built on Sept. 7, 2022, 5:07 p.m.