[−][src]Trait rv::traits::Support
Identifies the support of the Rv
Required methods
fn supports(&self, x: &X) -> bool
Returns true
if x
is in the support of the Rv
Example
use rv::dist::Uniform; use rv::traits::Support; // Create uniform with support on the interval [0, 1] let u = Uniform::new(0.0, 1.0).unwrap(); assert!(u.supports(&0.5_f64)); assert!(!u.supports(&-0.1_f64)); assert!(!u.supports(&1.1_f64));
Implementors
impl Support<bool> for Bernoulli
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impl Support<f32> for Beta
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impl Support<f32> for Cauchy
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impl Support<f32> for ChiSquared
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impl Support<f32> for Exponential
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impl Support<f32> for Gamma
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impl Support<f32> for Gaussian
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impl Support<f32> for Gev
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impl Support<f32> for InvGamma
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impl Support<f32> for Kumaraswamy
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impl Support<f32> for Laplace
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impl Support<f32> for LogNormal
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impl Support<f32> for Pareto
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impl Support<f32> for StudentsT
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impl Support<f32> for Uniform
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impl Support<f32> for VonMises
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impl Support<f64> for Beta
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impl Support<f64> for Cauchy
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impl Support<f64> for ChiSquared
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impl Support<f64> for Exponential
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impl Support<f64> for Gamma
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impl Support<f64> for Gaussian
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impl Support<f64> for Gev
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impl Support<f64> for InvGamma
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impl Support<f64> for Kumaraswamy
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impl Support<f64> for Laplace
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impl Support<f64> for LogNormal
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impl Support<f64> for Pareto
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impl Support<f64> for StudentsT
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impl Support<f64> for Uniform
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impl Support<f64> for VonMises
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impl Support<i16> for Bernoulli
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impl Support<i16> for BetaBinomial
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impl Support<i16> for Binomial
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impl Support<i32> for Bernoulli
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impl Support<i32> for BetaBinomial
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impl Support<i32> for Binomial
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impl Support<i64> for Bernoulli
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impl Support<i64> for BetaBinomial
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impl Support<i64> for Binomial
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impl Support<i8> for Bernoulli
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impl Support<i8> for BetaBinomial
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impl Support<i8> for Binomial
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impl Support<isize> for Bernoulli
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impl Support<u16> for Bernoulli
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impl Support<u16> for BetaBinomial
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impl Support<u16> for Binomial
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impl Support<u16> for Poisson
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impl Support<u32> for Bernoulli
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impl Support<u32> for BetaBinomial
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impl Support<u32> for Binomial
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impl Support<u32> for Poisson
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impl Support<u64> for Bernoulli
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impl Support<u64> for BetaBinomial
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impl Support<u64> for Binomial
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impl Support<u8> for Bernoulli
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impl Support<u8> for BetaBinomial
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impl Support<u8> for Binomial
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impl Support<u8> for Poisson
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impl Support<usize> for Bernoulli
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impl Support<usize> for BetaBinomial
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impl Support<usize> for Binomial
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impl Support<Partition> for Crp
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impl Support<Bernoulli> for Beta
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impl Support<Gaussian> for NormalGamma
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impl Support<MvGaussian> for NormalInvWishart
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fn supports(&self, x: &MvGaussian) -> bool
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impl Support<Poisson> for Gamma
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impl Support<Vec<f64>> for SymmetricDirichlet
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impl Support<Vec<f64>> for Dirichlet
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impl Support<Matrix<f64, Dynamic, Dynamic, <DefaultAllocator as Allocator<f64, Dynamic, Dynamic>>::Buffer>> for InvWishart
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impl Support<Matrix<f64, Dynamic, U1, VecStorage<f64, Dynamic, U1>>> for MvGaussian
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impl<X> Support<X> for Geometric where
X: Unsigned + Integer,
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X: Unsigned + Integer,
impl<X, Fx> Support<X> for Mixture<Fx> where
Fx: Rv<X> + Support<X>,
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Fx: Rv<X> + Support<X>,
impl<X, T> Support<X> for DiscreteUniform<T> where
X: Integer + From<T>,
T: DuParam,
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X: Integer + From<T>,
T: DuParam,