Struct statrs::distribution::FisherSnedecor
source · [−]pub struct FisherSnedecor { /* private fields */ }Expand description
Implements the Fisher-Snedecor distribution also commonly known as the F-distribution
Examples
use statrs::distribution::{FisherSnedecor, Continuous};
use statrs::statistics::Distribution;
use statrs::prec;
let n = FisherSnedecor::new(3.0, 3.0).unwrap();
assert_eq!(n.mean().unwrap(), 3.0);
assert!(prec::almost_eq(n.pdf(1.0), 0.318309886183790671538, 1e-15));Implementations
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());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);Trait Implementations
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
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
Calculates the cumulative distribution function for the fisher-snedecor
distribution
at x
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
Due to issues with rounding and floating-point accuracy the default
implementation may be ill-behaved.
Specialized inverse cdfs should be used whenever possible.
Performs a binary search on the domain of cdf to obtain an approximation
of F^-1(p) := inf { x | F(x) >= p }. Needless to say, performance may
may be lacking. Read more
Generate a random value of T, using rng as the source of randomness.
Create an iterator that generates random values of T, using rng as
the source of randomness. Read more
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
This method tests for self and other values to be equal, and is used
by ==. Read more
This method tests for !=.
Auto Trait Implementations
impl RefUnwindSafe for FisherSnedecor
impl Send for FisherSnedecor
impl Sync for FisherSnedecor
impl Unpin for FisherSnedecor
impl UnwindSafe for FisherSnedecor
Blanket Implementations
Mutably borrows from an owned value. Read more
The inverse inclusion map: attempts to construct self from the equivalent element of its
superset. Read more
Checks if self is actually part of its subset T (and can be converted to it).
Use with care! Same as self.to_subset but without any property checks. Always succeeds.
The inclusion map: converts self to the equivalent element of its superset.