[][src]Struct statrs::distribution::FisherSnedecor

pub struct FisherSnedecor { /* fields omitted */ }

Implements the Fisher-Snedecor distribution also commonly known as the F-distribution

Examples

use statrs::distribution::{FisherSnedecor, Continuous};
use statrs::statistics::Mean;
use statrs::prec;

let n = FisherSnedecor::new(3.0, 3.0).unwrap();
assert_eq!(n.mean(), 3.0);
assert!(prec::almost_eq(n.pdf(1.0), 0.318309886183790671538, 1e-15));

Methods

impl FisherSnedecor[src]

pub fn new(freedom_1: f64, freedom_2: f64) -> Result<FisherSnedecor>[src]

Constructs a new fisher-snedecor distribution with degrees of freedom freedom_1 and freedom_2

Errors

Returns an error if freedom_1 or freedom_2 are NaN. Also returns an error if freedom_1 <= 0.0 or freedom_2 <= 0.0

Examples

use statrs::distribution::FisherSnedecor;

let mut result = FisherSnedecor::new(1.0, 1.0);
assert!(result.is_ok());

result = FisherSnedecor::new(0.0, 0.0);
assert!(result.is_err());

pub fn freedom_1(&self) -> f64[src]

Returns the first degree of freedom for the fisher-snedecor distribution

Examples

use statrs::distribution::FisherSnedecor;

let n = FisherSnedecor::new(2.0, 3.0).unwrap();
assert_eq!(n.freedom_1(), 2.0);

pub fn freedom_2(&self) -> f64[src]

Returns the second degree of freedom for the fisher-snedecor distribution

Examples

use statrs::distribution::FisherSnedecor;

let n = FisherSnedecor::new(2.0, 3.0).unwrap();
assert_eq!(n.freedom_2(), 3.0);

Trait Implementations

impl Univariate<f64, f64> for FisherSnedecor[src]

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

Calculates the cumulative distribution function for the fisher-snedecor distribution at x

Formula

This example is not tested
I_((d1 * x) / (d1 * x + d2))(d1 / 2, d2 / 2)

where d1 is the first degree of freedom, d2 is the second degree of freedom, and I is the regularized incomplete beta function

impl Continuous<f64, f64> for FisherSnedecor[src]

fn pdf(&self, x: f64) -> f64[src]

Calculates the probability density function for the fisher-snedecor distribution at x

Remarks

Returns NaN if freedom_1, freedom_2 is INF, or x is +INF or -INF

Formula

This example is not tested
sqrt(((d1 * x) ^ d1 * d2 ^ d2) / (d1 * x + d2) ^ (d1 + d2)) / (x * β(d1
/ 2, d2 / 2))

where d1 is the first degree of freedom, d2 is the second degree of freedom, and β is the beta function

fn ln_pdf(&self, x: f64) -> f64[src]

Calculates the log probability density function for the fisher-snedecor distribution at x

Remarks

Returns NaN if freedom_1, freedom_2 is INF, or x is +INF or -INF

Formula

This example is not tested
ln(sqrt(((d1 * x) ^ d1 * d2 ^ d2) / (d1 * x + d2) ^ (d1 + d2)) / (x *
β(d1 / 2, d2 / 2)))

where d1 is the first degree of freedom, d2 is the second degree of freedom, and β is the beta function

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

This example is not tested
0

impl Max<f64> for FisherSnedecor[src]

fn max(&self) -> f64[src]

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

Formula

This example is not tested
INF

impl Mean<f64> for FisherSnedecor[src]

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

Returns the mean of the fisher-snedecor distribution

Panics

If freedom_2 <= 2.0

Remarks

Returns NaN if freedom_2 is INF

Formula

This example is not tested
d2 / (d2 - 2)

where d2 is the second degree of freedom

impl CheckedMean<f64> for FisherSnedecor[src]

fn checked_mean(&self) -> Result<f64>[src]

Returns the mean of the fisher-snedecor distribution

Errors

If freedom_2 <= 2.0

Remarks

Returns NaN if freedom_2 is INF

Formula

This example is not tested
d2 / (d2 - 2)

where d2 is the second degree of freedom

impl Variance<f64> for FisherSnedecor[src]

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

Returns the variance of the fisher-snedecor distribution

Panics

If freedom_2 <= 4.0

Remarks

Returns NaN if freedom_1 or freedom_2 is INF

Formula

This example is not tested
(2 * d2^2 * (d1 + d2 - 2)) / (d1 * (d2 - 2)^2 * (d2 - 4))

where d1 is the first degree of freedom and d2 is the second degree of freedom

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

Returns the standard deviation of the fisher-snedecor distribution

Panics

If freedom_2 <= 4.0

Remarks

Returns NaN if freedom_1 or freedom_2 is INF

Formula

This example is not tested
sqrt((2 * d2^2 * (d1 + d2 - 2)) / (d1 * (d2 - 2)^2 * (d2 - 4)))

where d1 is the first degree of freedom and d2 is the second degree of freedom

impl CheckedVariance<f64> for FisherSnedecor[src]

fn checked_variance(&self) -> Result<f64>[src]

Returns the variance of the fisher-snedecor distribution

Errors

If freedom_2 <= 4.0

Remarks

Returns NaN if freedom_1 or freedom_2 is INF

Formula

This example is not tested
(2 * d2^2 * (d1 + d2 - 2)) / (d1 * (d2 - 2)^2 * (d2 - 4))

where d1 is the first degree of freedom and d2 is the second degree of freedom

fn checked_std_dev(&self) -> Result<f64>[src]

Returns the standard deviation of the fisher-snedecor distribution

Errors

If freedom_2 <= 4.0

Remarks

Returns NaN if freedom_1 or freedom_2 is INF

Formula

This example is not tested
sqrt((2 * d2^2 * (d1 + d2 - 2)) / (d1 * (d2 - 2)^2 * (d2 - 4)))

where d1 is the first degree of freedom and d2 is the second degree of freedom

impl Skewness<f64> for FisherSnedecor[src]

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

Returns the skewness of the fisher-snedecor distribution

Panics

If freedom_2 <= 6.0

Remarks

Returns NaN if freedom_1 or freedom_2 is INF

Formula

This example is not tested
((2d1 + d2 - 2) * sqrt(8 * (d2 - 4))) / ((d2 - 6) * sqrt(d1 * (d1 + d2
- 2)))

where d1 is the first degree of freedom and d2 is the second degree of freedom

impl CheckedSkewness<f64> for FisherSnedecor[src]

fn checked_skewness(&self) -> Result<f64>[src]

Returns the skewness of the fisher-snedecor distribution

Errors

If freedom_2 <= 6.0

Remarks

Returns NaN if freedom_1 or freedom_2 is INF

Formula

This example is not tested
((2d1 + d2 - 2) * sqrt(8 * (d2 - 4))) / ((d2 - 6) * sqrt(d1 * (d1 + d2
- 2)))

where d1 is the first degree of freedom and d2 is the second degree of freedom

impl Mode<f64> for FisherSnedecor[src]

fn mode(&self) -> f64[src]

Returns the mode for the fisher-snedecor distribution

Panics

If freedom_1 <= 2.0

Remarks

Returns NaN if freedom_1 or freedom_2 is INF

Formula

This example is not tested
((d1 - 2) / d1) * (d2 / (d2 + 2))

where d1 is the first degree of freedom and d2 is the second degree of freedom

impl CheckedMode<f64> for FisherSnedecor[src]

fn checked_mode(&self) -> Result<f64>[src]

Returns the mode for the fisher-snedecor distribution

Errors

If freedom_1 <= 2.0

Remarks

Returns NaN if freedom_1 or freedom_2 is INF

Formula

This example is not tested
((d1 - 2) / d1) * (d2 / (d2 + 2))

where d1 is the first degree of freedom and d2 is the second degree of freedom

impl Copy for FisherSnedecor[src]

impl PartialEq<FisherSnedecor> for FisherSnedecor[src]

impl Clone for FisherSnedecor[src]

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

Performs copy-assignment from source. Read more

impl Debug for FisherSnedecor[src]

impl Distribution<f64> for FisherSnedecor[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

Auto Trait Implementations

Blanket Implementations

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

type Owned = T

The resulting type after obtaining ownership.

impl<T> From<T> for T[src]

impl<T, U> Into<U> for T where
    U: From<T>, 
[src]

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.

impl<T> BorrowMut<T> for T where
    T: ?Sized
[src]

impl<T> Borrow<T> for T where
    T: ?Sized
[src]

impl<T> Any for T where
    T: 'static + ?Sized
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