pub trait Mode<T> {
fn mode(&self) -> T;
}The Mode trait specififies that an object has a closed form solution
for its mode(s)
Returns the mode. May panic depending on
the implementor.
use statrs::statistics::Mode;
use statrs::distribution::Uniform;
let n = Uniform::new(0.0, 1.0).unwrap();
assert_eq!(0.5, n.mode());
Returns the mode of the Beta distribution.
Since the mode is technically only calculate for α > 1, β > 1, those
are the only values we allow. We may consider relaxing this constraint
in
the future.
If α <= 1 or β <= 1
where α is shapeA and β is shapeB
Returns the mode of the cauchy distribution
where x_0 is the location
Returns the mode for the chi distribution
If freedom < 1.0
where k is the degrees of freedom
Returns the mode of the chi-squared distribution
where k is the degrees of freedom
Returns the mode for the erlang distribution
Returns shape if rate ==f64::INFINITY. This behavior
is borrowed from the Math.NET implementation
where k is the shape and λ is the rate
Returns the mode of the exponential distribution
Returns the mode for the fisher-snedecor distribution
If freedom_1 <= 2.0
Returns NaN if freedom_1 or freedom_2 is INF
((d1 - 2) / d1) * (d2 / (d2 + 2))
where d1 is the first degree of freedom and d2 is
the second degree of freedom
Returns the mode for the gamma distribution
Returns shape if rate ==f64::INFINITY. This behavior
is borrowed from the Math.NET implementation
where α is the shape and β is the rate
Returns the mode of the inverse gamma distribution
/// where α is the shape and β is the rate
Returns the mode of the log-normal distribution
where μ is the location and σ is the scale
Returns the mode of the normal distribution
where μ is the mean
Returns the mode of the Pareto distribution
where x_m is the scale
Returns the mode of the student’s t-distribution
where μ is the location
Returns the mode of the triangular distribution
Returns the mode for the continuous uniform distribution
Since every element has an equal probability, mode simply
returns the middle element
Returns the median of the weibull distribution
if k == 1 {
0
} else {
λ((k - 1) / k)^(1 / k)
}where k is the shape and λ is the scale
Returns the mode for the discrete uniform distribution
Since every element has an equal probability, mode simply
returns the middle element
Returns the mode of the bernoulli distribution
if p < 0.5 { 0 }
else { 1 }
Returns the mode for the binomial distribution
Returns the mode of the geometric distribution
Returns the mode of the hypergeometric distribution
floor((n + 1) * (k + 1) / (N + 2))
where N is population, K is successes, and n is draws
Returns the mode of the poisson distribution
where λ is the rate