# [−][src]Struct statrs::distribution::Bernoulli

`pub struct Bernoulli { /* fields omitted */ }`

Implements the Bernoulli distribution which is a special case of the Binomial distribution where `n = 1` (referenced Here)

# Examples

```use statrs::distribution::{Bernoulli, Discrete};
use statrs::statistics::Mean;

let n = Bernoulli::new(0.5).unwrap();
assert_eq!(n.mean(), 0.5);
assert_eq!(n.pmf(0), 0.5);
assert_eq!(n.pmf(1), 0.5);```

## Methods

### `impl Bernoulli`[src]

#### `pub fn new(p: f64) -> Result<Bernoulli>`[src]

Constructs a new bernoulli distribution with the given `p` probability of success.

# Errors

Returns an error if `p` is `NaN`, less than `0.0` or greater than `1.0`

# Examples

```use statrs::distribution::Bernoulli;

let mut result = Bernoulli::new(0.5);
assert!(result.is_ok());

result = Bernoulli::new(-0.5);
assert!(result.is_err());```

#### `pub fn p(&self) -> f64`[src]

Returns the probability of success `p` of the bernoulli distribution.

# Examples

```use statrs::distribution::Bernoulli;

let n = Bernoulli::new(0.5).unwrap();
assert_eq!(n.p(), 0.5);```

#### `pub fn n(&self) -> u64`[src]

Returns the number of trials `n` of the bernoulli distribution. Will always be `1.0`.

# Examples

```use statrs::distribution::Bernoulli;

let n = Bernoulli::new(0.5).unwrap();
assert_eq!(n.n(), 1);```

## Trait Implementations

### `impl Univariate<u64, f64> for Bernoulli`[src]

#### `fn cdf(&self, x: f64) -> f64`[src]

Calculates the cumulative distribution function for the bernoulli distribution at `x`.

# Formula

```if x < 0 { 0 }
else if x >= 1 { 1 }
else { 1 - p }```

### `impl Discrete<u64, f64> for Bernoulli`[src]

#### `fn pmf(&self, x: u64) -> f64`[src]

Calculates the probability mass function for the bernoulli distribution at `x`.

# Formula

```if x == 0 { 1 - p }
else { p }```

#### `fn ln_pmf(&self, x: u64) -> f64`[src]

Calculates the log probability mass function for the bernoulli distribution at `x`.

# Formula

```else if x == 0 { ln(1 - p) }
else { ln(p) }```

### `impl Min<u64> for Bernoulli`[src]

#### `fn min(&self) -> u64`[src]

Returns the minimum value in the domain of the bernoulli distribution representable by a 64- bit integer

# Formula

`0`

### `impl Max<u64> for Bernoulli`[src]

#### `fn max(&self) -> u64`[src]

Returns the maximum value in the domain of the bernoulli distribution representable by a 64- bit integer

# Formula

`1`

### `impl Mean<f64> for Bernoulli`[src]

#### `fn mean(&self) -> f64`[src]

Returns the mean of the bernoulli distribution

# Formula

`p`

### `impl Variance<f64> for Bernoulli`[src]

#### `fn variance(&self) -> f64`[src]

Returns the variance of the bernoulli distribution

# Formula

`p * (1 - p)`

#### `fn std_dev(&self) -> f64`[src]

Returns the standard deviation of the bernoulli distribution

# Formula

`sqrt(p * (1 - p))`

### `impl Entropy<f64> for Bernoulli`[src]

#### `fn entropy(&self) -> f64`[src]

Returns the entropy of the bernoulli distribution

# Formula

```q = (1 - p)
-q * ln(q) - p * ln(p)```

### `impl Skewness<f64> for Bernoulli`[src]

#### `fn skewness(&self) -> f64`[src]

Returns the skewness of the bernoulli distribution

# Formula

```q = (1 - p)
(1 - 2p) / sqrt(p * q)```

### `impl Median<f64> for Bernoulli`[src]

#### `fn median(&self) -> f64`[src]

Returns the median of the bernoulli distribution

# Formula

```if p < 0.5 { 0 }
else if p > 0.5 { 1 }
else { 0.5 }```

### `impl Mode<u64> for Bernoulli`[src]

#### `fn mode(&self) -> u64`[src]

Returns the mode of the bernoulli distribution

# Formula

```if p < 0.5 { 0 }
else { 1 }```

### `impl Clone for Bernoulli`[src]

#### `fn clone_from(&mut self, source: &Self)`1.0.0[src]

Performs copy-assignment from `source`. Read more

### `impl Distribution<f64> for Bernoulli`[src]

#### `fn sample_iter<R>(&'a self, rng: &'a mut R) -> DistIter<'a, Self, R, T> where    R: Rng, `[src]

Create an iterator that generates random values of `T`, using `rng` as the source of randomness. Read more

## Blanket Implementations

### `impl<T> ToOwned for T where    T: Clone, `[src]

#### `type Owned = T`

The resulting type after obtaining ownership.

### `impl<T, U> TryFrom<U> for T where    U: Into<T>, `[src]

#### `type Error = Infallible`

The type returned in the event of a conversion error.

### `impl<T, U> TryInto<U> for T where    U: TryFrom<T>, `[src]

#### `type Error = <U as TryFrom<T>>::Error`

The type returned in the event of a conversion error.