# [−][src]Trait statrs::statistics::Min

```pub trait Min<T> {
fn min(&self) -> T;
}```

The `Min` trait specifies than an object has a minimum value

## Required methods

### `fn min(&self) -> T`

Returns the minimum value in the domain of a given distribution representable by a double-precision float. May panic depending on the implementor.

# Examples

```use statrs::statistics::Min;
use statrs::distribution::Uniform;

let n = Uniform::new(0.0, 1.0).unwrap();
assert_eq!(0.0, n.min());```

## Implementations on Foreign Types

### `impl Min<f64> for [f64]`[src]

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

Returns the minimum value in the data

# Remarks

Returns `f64::NAN` if data is empty or an entry is `f64::NAN`

# Examples

```use std::f64;
use statrs::statistics::Min;

let x: [f64; 0] = [];
assert!(x.min().is_nan());

let y = [0.0, f64::NAN, 3.0, -2.0];
assert!(y.min().is_nan());

let z = [0.0, 3.0, -2.0];
assert_eq!(z.min(), -2.0);```

## Implementors

### `impl Min<f64> for Beta`[src]

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

Returns the minimum value in the domain of the beta distribution representable by a double precision float

# Formula

`0`

### `impl Min<f64> for Cauchy`[src]

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

Returns the minimum value in the domain of the cauchy distribution representable by a double precision float

# Formula

`NEG_INF`

### `impl Min<f64> for Chi`[src]

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

Returns the minimum value in the domain of the chi distribution representable by a double precision float

# Formula

`0`

### `impl Min<f64> for ChiSquared`[src]

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

Returns the minimum value in the domain of the chi-squared distribution representable by a double precision float

# Formula

`0`

### `impl Min<f64> for Erlang`[src]

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

Returns the minimum value in the domain of the erlang distribution representable by a double precision float

# Formula

`0`

### `impl Min<f64> for Exponential`[src]

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

Returns the minimum value in the domain of the exponential distribution representable by a double precision float

# Formula

`0`

### `impl Min<f64> for FisherSnedecor`[src]

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

Returns the minimum value in the domain of the fisher-snedecor distribution representable by a double precision float

# Formula

`0`

### `impl Min<f64> for Gamma`[src]

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

Returns the minimum value in the domain of the gamma distribution representable by a double precision float

# Formula

`0`

### `impl Min<f64> for InverseGamma`[src]

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

Returns the minimum value in the domain of the inverse gamma distribution representable by a double precision float

# Formula

`0`

### `impl Min<f64> for LogNormal`[src]

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

Returns the minimum value in the domain of the log-normal distribution representable by a double precision float

# Formula

`0`

### `impl Min<f64> for Normal`[src]

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

Returns the minimum value in the domain of the normal distribution representable by a double precision float

# Formula

`-INF`

### `impl Min<f64> for Pareto`[src]

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

Returns the minimum value in the domain of the Pareto distribution representable by a double precision float

# Formula

`x_m`

where `x_m` is the scale

### `impl Min<f64> for StudentsT`[src]

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

Returns the minimum value in the domain of the student's t-distribution representable by a double precision float

# Formula

`-INF`

### `impl Min<f64> for Triangular`[src]

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

Returns the minimum value in the domain of the triangular distribution representable by a double precision float

# Remarks

The return value is the same min used to construct the distribution

### `impl Min<f64> for Weibull`[src]

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

Returns the minimum value in the domain of the weibull distribution representable by a double precision float

# Formula

`0`

### `impl Min<i64> for DiscreteUniform`[src]

#### `fn min(&self) -> i64`[src]

Returns the minimum value in the domain of the discrete uniform distribution

# Remarks

This is the same value as the minimum passed into the constructor

### `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 Min<u64> for Binomial`[src]

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

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

# Formula

`0`

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

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

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

# Formula

`0`

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

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

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

# Formula

`1`

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

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

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

# Formula

`max(0, n + K - N)`

where `N` is population, `K` is successes, and `n` is draws

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

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

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

`0`