Struct statrs::distribution::FisherSnedecor
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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
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fn new(freedom_1: f64, freedom_2: f64) -> Result<FisherSnedecor>
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());
fn freedom_1(&self) -> f64
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);
fn freedom_2(&self) -> f64
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 Debug for FisherSnedecor
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impl Copy for FisherSnedecor
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impl Clone for FisherSnedecor
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fn clone(&self) -> FisherSnedecor
Returns a copy of the value. Read more
fn clone_from(&mut self, source: &Self)
1.0.0
Performs copy-assignment from source
. Read more
impl PartialEq for FisherSnedecor
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fn eq(&self, __arg_0: &FisherSnedecor) -> bool
This method tests for self
and other
values to be equal, and is used by ==
. Read more
fn ne(&self, __arg_0: &FisherSnedecor) -> bool
This method tests for !=
.
impl Sample<f64> for FisherSnedecor
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fn sample<R: Rng>(&mut self, r: &mut R) -> f64
Generate a random sample from a fisher-snedecor distribution
using r
as the source of randomness.
Refer here for implementation details.
impl IndependentSample<f64> for FisherSnedecor
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fn ind_sample<R: Rng>(&self, r: &mut R) -> f64
Generate a random independent sample from a fisher-snedecor distribution
using r
as the source of randomness.
Refer here for implementation details.
impl Distribution<f64> for FisherSnedecor
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fn sample<R: Rng>(&self, r: &mut R) -> f64
Generate a random sample from a fisher-snedecor distribution using
r
as the source of randomness.
Examples
use rand::StdRng; use statrs::distribution::{FisherSnedecor, Distribution}; let mut r = rand::StdRng::new().unwrap(); let n = FisherSnedecor::new(2.0, 2.0).unwrap(); print!("{}", n.sample::<StdRng>(&mut r));
impl Univariate<f64, f64> for FisherSnedecor
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fn cdf(&self, x: f64) -> f64
Calculates the cumulative distribution function for the fisher-snedecor distribution
at x
Panics
If x
is not in [0, +inf)
Formula
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 Min<f64> for FisherSnedecor
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fn min(&self) -> f64
Returns the minimum value in the domain of the fisher-snedecor distribution representable by a double precision float
Formula
0
impl Max<f64> for FisherSnedecor
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fn max(&self) -> f64
Returns the maximum value in the domain of the fisher-snedecor distribution representable by a double precision float
Formula
INF
impl Mean<f64> for FisherSnedecor
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impl Variance<f64> for FisherSnedecor
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fn variance(&self) -> f64
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
(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
impl Skewness<f64> for FisherSnedecor
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fn skewness(&self) -> f64
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
((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
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impl Continuous<f64, f64> for FisherSnedecor
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fn pdf(&self, x: f64) -> f64
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
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
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
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