[−][src]Trait rstat::ContinuousDistribution
Trait for distributions with an absolutely continuous CDF.
The PDF can be interpreted as the relative likelihood that a random variable \(X\) takes on a value equal to \(x\). For absolutely continuous univariate distributions it is defined by the derivative of the CDF, i.e \(f(x) = F'(x)\). Intuitively, one may think of \(f(x)\text{d}x\) that as representing the probability that the random variable \(X\) lies in the infinitesimal interval \([x, x + \text{d}x]\). Alternatively, one can interpret the PDF, for infinitesimally small \(\text{d}t\), as: \(f(t)\text{d}t = P(t < X < t + \text{d}t)\). For a finite interval \([a, b],\) we have that: \[P(a < X < b) = \int_a^b f(t)\text{d}t.\]
Provided methods
fn pdf(&self, x: &Sample<Self>) -> f64
Evaluates the probability density function (PDF) at \(x\).
Examples
let dist = Triangular::new_unchecked(0.0, 0.5, 0.5); assert_eq!(dist.pdf(&0.0), 0.0); assert_eq!(dist.pdf(&0.25), 1.0); assert_eq!(dist.pdf(&0.5), 2.0); assert_eq!(dist.pdf(&0.75), 1.0); assert_eq!(dist.pdf(&1.0), 0.0);
fn log_pdf(&self, x: &Sample<Self>) -> f64
Evaluates the log PDF at \(x\).
Implementors
impl ContinuousDistribution for Dirichlet
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impl ContinuousDistribution for BvNormal
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impl ContinuousDistribution for MvNormal
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impl ContinuousDistribution for PairedNormal
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impl ContinuousDistribution for UvNormal
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impl ContinuousDistribution for Arcsine
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impl ContinuousDistribution for Beta
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impl ContinuousDistribution for BetaPrime
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impl ContinuousDistribution for Cauchy
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impl ContinuousDistribution for Chi
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impl ContinuousDistribution for ChiSq
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impl ContinuousDistribution for Cosine
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impl ContinuousDistribution for Erlang
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impl ContinuousDistribution for Exponential
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impl ContinuousDistribution for FDist
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impl ContinuousDistribution for FoldedNormal
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impl ContinuousDistribution for Frechet
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impl ContinuousDistribution for Gamma
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impl ContinuousDistribution for GeneralisedExtremeValue
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impl ContinuousDistribution for GeneralisedPareto
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impl ContinuousDistribution for Gumbel
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impl ContinuousDistribution for InvGamma
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impl ContinuousDistribution for InvNormal
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impl ContinuousDistribution for Kumaraswamy
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impl ContinuousDistribution for Laplace
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impl ContinuousDistribution for Levy
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impl ContinuousDistribution for Logistic
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impl ContinuousDistribution for Pareto
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impl ContinuousDistribution for Rayleigh
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impl ContinuousDistribution for StudentT
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impl ContinuousDistribution for Triangular
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impl ContinuousDistribution for Uniform<f64>
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impl ContinuousDistribution for Weibull
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impl ContinuousDistribution for DiagonalNormal
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impl ContinuousDistribution for IsotropicNormal
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impl<C: ContinuousDistribution> ContinuousDistribution for Mixture<C> where
C::Support: Union + Clone,
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C::Support: Union + Clone,
impl<S> ContinuousDistribution for LogNormal<S> where
Normal<Vector<f64>, S>: From<Params<S>> + Distribution<Support = ProductSpace<Reals>, Params = Params<S>>,
Normal<Vector<f64>, S>: ContinuousDistribution,
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Normal<Vector<f64>, S>: From<Params<S>> + Distribution<Support = ProductSpace<Reals>, Params = Params<S>>,
Normal<Vector<f64>, S>: ContinuousDistribution,