[−][src]Trait statrs::statistics::Mode
The Mode
trait specififies that an object has a closed form solution
for its mode(s)
Required methods
fn mode(&self) -> T
Returns the mode. May panic depending on the implementor.
Examples
use statrs::statistics::Mode; use statrs::distribution::Uniform; let n = Uniform::new(0.0, 1.0).unwrap(); assert_eq!(0.5, n.mode());
Implementors
impl Mode<f64> for Beta
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fn mode(&self) -> f64
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Returns the mode of the Beta distribution.
Remarks
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.
Panics
If α <= 1
or β <= 1
Formula
(α - 1) / (α + β - 2)
where α
is shapeA and β
is shapeB
impl Mode<f64> for Cauchy
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fn mode(&self) -> f64
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Returns the mode of the cauchy distribution
Formula
x_0
where x_0
is the location
impl Mode<f64> for Chi
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impl Mode<f64> for ChiSquared
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fn mode(&self) -> f64
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Returns the mode of the chi-squared distribution
Formula
k - 2
where k
is the degrees of freedom
impl Mode<f64> for Dirac
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fn mode(&self) -> f64
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Returns the mode of the dirac distribution
Formula
v
where v
is the point of the dirac distribution
impl Mode<f64> for Erlang
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impl Mode<f64> for Exponential
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impl Mode<f64> for FisherSnedecor
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impl Mode<f64> for Gamma
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impl Mode<f64> for InverseGamma
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fn mode(&self) -> f64
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Returns the mode of the inverse gamma distribution
Formula
β / (α + 1)
/// where α
is the shape and β
is the rate
impl Mode<f64> for LogNormal
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fn mode(&self) -> f64
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Returns the mode of the log-normal distribution
Formula
e^(μ - σ^2)
where μ
is the location and σ
is the scale
impl Mode<f64> for NegativeBinomial
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fn mode(&self) -> f64
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Returns the mode for the negative binomial distribution
Formula
if r > 1 then floor((r - 1) * (1-p / p)) else 0
impl Mode<f64> for Normal
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fn mode(&self) -> f64
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Returns the mode of the normal distribution
Formula
μ
where μ
is the mean
impl Mode<f64> for Pareto
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fn mode(&self) -> f64
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Returns the mode of the Pareto distribution
Formula
x_m
where x_m
is the scale
impl Mode<f64> for StudentsT
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fn mode(&self) -> f64
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Returns the mode of the student's t-distribution
Formula
μ
where μ
is the location
impl Mode<f64> for Triangular
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impl Mode<f64> for Uniform
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impl Mode<f64> for Weibull
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fn mode(&self) -> f64
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Returns the median of the weibull distribution
Formula
if k == 1 { 0 } else { λ((k - 1) / k)^(1 / k) }
where k
is the shape and λ
is the scale
impl Mode<i64> for DiscreteUniform
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impl Mode<u64> for Bernoulli
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fn mode(&self) -> u64
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Returns the mode of the bernoulli distribution
Formula
if p < 0.5 { 0 } else { 1 }
impl Mode<u64> for Binomial
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fn mode(&self) -> u64
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Returns the mode for the binomial distribution
Formula
floor((n + 1) * p)
impl Mode<u64> for Geometric
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impl Mode<u64> for Hypergeometric
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fn mode(&self) -> u64
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Returns the mode of the hypergeometric distribution
Formula
floor((n + 1) * (k + 1) / (N + 2))
where N
is population, K
is successes, and n
is draws
impl Mode<u64> for Poisson
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fn mode(&self) -> u64
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Returns the mode of the poisson distribution
Formula
floor(λ)
where λ
is the rate
impl<N> Mode<Matrix<f64, N, U1, <DefaultAllocator as Allocator<f64, N, U1>>::Buffer>> for MultivariateNormal<N> where
N: Dim + DimMin<N, Output = N> + DimName,
DefaultAllocator: Allocator<f64, N>,
DefaultAllocator: Allocator<f64, N, N>,
DefaultAllocator: Allocator<f64, U1, N>,
DefaultAllocator: Allocator<(usize, usize), <N as DimMin<N>>::Output>,
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N: Dim + DimMin<N, Output = N> + DimName,
DefaultAllocator: Allocator<f64, N>,
DefaultAllocator: Allocator<f64, N, N>,
DefaultAllocator: Allocator<f64, U1, N>,
DefaultAllocator: Allocator<(usize, usize), <N as DimMin<N>>::Output>,