[−][src]Trait rv::traits::InverseCdf
Has an inverse-CDF / quantile function
Required methods
fn invcdf(&self, p: f64) -> X
The value of the x
at the given probability in the CDF
Example
The CDF identity: p = CDF(x) => x = CDF-1(p)
use rv::dist::Gaussian; use rv::traits::Cdf; use rv::traits::InverseCdf; let g = Gaussian::standard(); let x: f64 = 1.2; let p: f64 = g.cdf(&x); let y: f64 = g.invcdf(p); // x and y should be about the same assert!((x - y).abs() < 1E-12);
Provided methods
fn quantile(&self, p: f64) -> X
Alias for invcdf
fn interval(&self, p: f64) -> (X, X)
Interval containing p
proportion for the probability
Example
Confidence interval
use rv::dist::Gaussian; use rv::traits::InverseCdf; let g = Gaussian::new(100.0, 15.0).unwrap(); let ci: (f64, f64) = g.interval(0.68268949213708585); // one stddev assert!( (ci.0 - 85.0).abs() < 1E-12); assert!( (ci.1 - 115.0).abs() < 1E-12);
Implementors
impl InverseCdf<f32> for Cauchy
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impl InverseCdf<f32> for Exponential
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impl InverseCdf<f32> for Gaussian
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impl InverseCdf<f32> for KsTwoAsymptotic
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impl InverseCdf<f32> for Kumaraswamy
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impl InverseCdf<f32> for LogNormal
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impl InverseCdf<f32> for Uniform
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impl InverseCdf<f64> for Cauchy
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impl InverseCdf<f64> for Exponential
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impl InverseCdf<f64> for Gaussian
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impl InverseCdf<f64> for KsTwoAsymptotic
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impl InverseCdf<f64> for Kumaraswamy
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impl InverseCdf<f64> for LogNormal
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impl InverseCdf<f64> for Uniform
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impl<Fx, X> InverseCdf<X> for Fx where
Fx: Deref,
Fx::Target: InverseCdf<X>,
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Fx: Deref,
Fx::Target: InverseCdf<X>,
fn invcdf(&self, p: f64) -> X
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fn quantile(&self, p: f64) -> X
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fn interval(&self, p: f64) -> (X, X)
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impl<X, T> InverseCdf<X> for DiscreteUniform<T> where
X: Integer + From<T> + FromPrimitive,
T: DuParam + SampleUniform + ToPrimitive,
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X: Integer + From<T> + FromPrimitive,
T: DuParam + SampleUniform + ToPrimitive,