[−][src]Struct rv::dist::Beta
Beta distribution, Beta(α, β) over x in (0, 1).
Examples
Beta as a conjugate prior for Bernoulli
use rv::prelude::*; // A prior that encodes our strong belief that coins are fair: let beta = Beta::new(5.0, 5.0).unwrap(); // The posterior predictive probability that a coin will come up heads given // no new observations. let p_prior_heads = beta.pp(&true, &DataOrSuffStat::None); // 0.5 assert!((p_prior_heads - 0.5).abs() < 1E-12); // Five Bernoulli trials. We flipped a coin five times and it came up head // four times. let flips = vec![true, true, false, true, true]; // The posterior predictive probability that a coin will come up heads given // the five flips we just saw. let p_pred_heads = beta.pp(&true, &DataOrSuffStat::Data(&flips)); // 9/15 assert!((p_pred_heads - 3.0/5.0).abs() < 1E-12);
Implementations
impl Beta
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pub fn new(alpha: f64, beta: f64) -> Result<Self, BetaError>
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Create a Beta
distribution with even density over (0, 1).
Example
// Uniform let beta_unif = Beta::new(1.0, 1.0); assert!(beta_unif.is_ok()); // Jefferey's prior let beta_jeff = Beta::new(0.5, 0.5); assert!(beta_jeff.is_ok()); // Invalid negative parameter let beta_nope = Beta::new(-5.0, 1.0); assert!(beta_nope.is_err());
pub fn new_unchecked(alpha: f64, beta: f64) -> Self
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Creates a new Beta without checking whether the parameters are valid.
pub fn uniform() -> Self
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Create a Beta
distribution with even density over (0, 1).
Example
let beta = Beta::uniform(); assert_eq!(beta, Beta::new(1.0, 1.0).unwrap());
pub fn jeffreys() -> Self
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Create a Beta
distribution with the Jeffrey's parameterization,
Beta(0.5, 0.5).
Example
let beta = Beta::jeffreys(); assert_eq!(beta, Beta::new(0.5, 0.5).unwrap());
pub fn alpha(&self) -> f64
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Get the alpha parameter
Example
let beta = Beta::new(1.0, 5.0).unwrap(); assert_eq!(beta.alpha(), 1.0);
pub fn set_alpha(&mut self, alpha: f64) -> Result<(), BetaError>
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Set the alpha parameter
Example
let mut beta = Beta::new(1.0, 5.0).unwrap(); beta.set_alpha(2.0).unwrap(); assert_eq!(beta.alpha(), 2.0);
Will error for invalid values
assert!(beta.set_alpha(0.1).is_ok()); assert!(beta.set_alpha(0.0).is_err()); assert!(beta.set_alpha(-1.0).is_err()); assert!(beta.set_alpha(std::f64::INFINITY).is_err()); assert!(beta.set_alpha(std::f64::NAN).is_err());
pub fn set_alpha_unchecked(&mut self, alpha: f64)
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Set alpha without input validation
pub fn beta(&self) -> f64
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Get the beta parameter
Example
let beta = Beta::new(1.0, 5.0).unwrap(); assert_eq!(beta.beta(), 5.0);
pub fn set_beta(&mut self, beta: f64) -> Result<(), BetaError>
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Set the beta parameter
Example
let mut beta = Beta::new(1.0, 5.0).unwrap(); beta.set_beta(2.0).unwrap(); assert_eq!(beta.beta(), 2.0);
Will error for invalid values
assert!(beta.set_beta(0.1).is_ok()); assert!(beta.set_beta(0.0).is_err()); assert!(beta.set_beta(-1.0).is_err()); assert!(beta.set_beta(std::f64::INFINITY).is_err()); assert!(beta.set_beta(std::f64::NAN).is_err());
pub fn set_beta_unchecked(&mut self, beta: f64)
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Set beta without input validation
Trait Implementations
impl Cdf<f32> for Beta
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impl Cdf<f64> for Beta
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impl Clone for Beta
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fn clone(&self) -> Self
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fn clone_from(&mut self, source: &Self)
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impl<X: Booleable> ConjugatePrior<X, Bernoulli> for Beta
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type Posterior = Self
fn posterior(&self, x: &DataOrSuffStat<X, Bernoulli>) -> Self
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fn ln_m(&self, x: &DataOrSuffStat<X, Bernoulli>) -> f64
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fn ln_pp(&self, y: &X, x: &DataOrSuffStat<X, Bernoulli>) -> f64
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fn m(&self, x: &DataOrSuffStat<X, Fx>) -> f64
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fn pp(&self, y: &X, x: &DataOrSuffStat<X, Fx>) -> f64
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impl ConjugatePrior<bool, Bernoulli> for Beta
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type Posterior = Self
fn posterior(&self, x: &DataOrSuffStat<bool, Bernoulli>) -> Self
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fn ln_m(&self, x: &DataOrSuffStat<bool, Bernoulli>) -> f64
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fn ln_pp(&self, y: &bool, x: &DataOrSuffStat<bool, Bernoulli>) -> f64
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fn m(&self, x: &DataOrSuffStat<X, Fx>) -> f64
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fn pp(&self, y: &X, x: &DataOrSuffStat<X, Fx>) -> f64
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impl ContinuousDistr<Bernoulli> for Beta
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impl ContinuousDistr<f32> for Beta
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impl ContinuousDistr<f64> for Beta
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impl Debug for Beta
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impl Default for Beta
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impl Display for Beta
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impl Entropy for Beta
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impl<'_> From<&'_ Beta> for String
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impl Kurtosis for Beta
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impl Mean<f32> for Beta
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impl Mean<f64> for Beta
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impl Mode<f32> for Beta
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impl Mode<f64> for Beta
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impl PartialEq<Beta> for Beta
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impl Rv<Bernoulli> for Beta
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fn ln_f(&self, x: &Bernoulli) -> f64
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fn draw<R: Rng>(&self, rng: &mut R) -> Bernoulli
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fn f(&self, x: &X) -> f64
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fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<X>
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fn sample_stream<'r, R: Rng>(
&'r self,
rng: &'r mut R
) -> Box<dyn Iterator<Item = X> + 'r>
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&'r self,
rng: &'r mut R
) -> Box<dyn Iterator<Item = X> + 'r>
impl Rv<f32> for Beta
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fn ln_f(&self, x: &f32) -> f64
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fn draw<R: Rng>(&self, rng: &mut R) -> f32
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fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<f32>
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fn f(&self, x: &X) -> f64
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fn sample_stream<'r, R: Rng>(
&'r self,
rng: &'r mut R
) -> Box<dyn Iterator<Item = X> + 'r>
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&'r self,
rng: &'r mut R
) -> Box<dyn Iterator<Item = X> + 'r>
impl Rv<f64> for Beta
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fn ln_f(&self, x: &f64) -> f64
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fn draw<R: Rng>(&self, rng: &mut R) -> f64
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fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<f64>
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fn f(&self, x: &X) -> f64
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fn sample_stream<'r, R: Rng>(
&'r self,
rng: &'r mut R
) -> Box<dyn Iterator<Item = X> + 'r>
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&'r self,
rng: &'r mut R
) -> Box<dyn Iterator<Item = X> + 'r>
impl Skewness for Beta
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impl Support<Bernoulli> for Beta
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impl Support<f32> for Beta
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impl Support<f64> for Beta
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impl Variance<f64> for Beta
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Auto Trait Implementations
impl RefUnwindSafe for Beta
impl Send for Beta
impl Sync for Beta
impl Unpin for Beta
impl UnwindSafe for Beta
Blanket Implementations
impl<T> Any for T where
T: 'static + ?Sized,
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T: 'static + ?Sized,
impl<T> Borrow<T> for T where
T: ?Sized,
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T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
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T: ?Sized,
fn borrow_mut(&mut self) -> &mut T
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impl<Fx, X> Cdf<X> for Fx where
Fx: Deref,
<Fx as Deref>::Target: Cdf<X>,
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Fx: Deref,
<Fx as Deref>::Target: Cdf<X>,
impl<Fx, X> ContinuousDistr<X> for Fx where
Fx: Deref,
<Fx as Deref>::Target: ContinuousDistr<X>,
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Fx: Deref,
<Fx as Deref>::Target: ContinuousDistr<X>,
impl<Fx> Entropy for Fx where
Fx: Deref,
<Fx as Deref>::Target: Entropy,
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Fx: Deref,
<Fx as Deref>::Target: Entropy,
impl<T> From<T> for T
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impl<T, U> Into<U> for T where
U: From<T>,
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U: From<T>,
impl<Fx> Kurtosis for Fx where
Fx: Deref,
<Fx as Deref>::Target: Kurtosis,
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Fx: Deref,
<Fx as Deref>::Target: Kurtosis,
impl<Fx, X> Mean<X> for Fx where
Fx: Deref,
<Fx as Deref>::Target: Mean<X>,
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Fx: Deref,
<Fx as Deref>::Target: Mean<X>,
impl<Fx, X> Mode<X> for Fx where
Fx: Deref,
<Fx as Deref>::Target: Mode<X>,
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Fx: Deref,
<Fx as Deref>::Target: Mode<X>,
impl<Fx, X> Rv<X> for Fx where
Fx: Deref,
<Fx as Deref>::Target: Rv<X>,
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Fx: Deref,
<Fx as Deref>::Target: Rv<X>,
fn ln_f(&Self, &X) -> f64
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fn f(&Self, &X) -> f64
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fn draw<R>(&Self, &mut R) -> X where
R: Rng,
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R: Rng,
fn sample<R>(&Self, usize, &mut R) -> Vec<X> where
R: Rng,
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R: Rng,
fn sample_stream<'r, R: Rng>(
&'r self,
rng: &'r mut R
) -> Box<dyn Iterator<Item = X> + 'r>
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&'r self,
rng: &'r mut R
) -> Box<dyn Iterator<Item = X> + 'r>
impl<T> Same<T> for T
type Output = T
Should always be Self
impl<Fx> Skewness for Fx where
Fx: Deref,
<Fx as Deref>::Target: Skewness,
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Fx: Deref,
<Fx as Deref>::Target: Skewness,
impl<SS, SP> SupersetOf<SS> for SP where
SS: SubsetOf<SP>,
SS: SubsetOf<SP>,
fn to_subset(&self) -> Option<SS>
fn is_in_subset(&self) -> bool
unsafe fn to_subset_unchecked(&self) -> SS
fn from_subset(element: &SS) -> SP
impl<Fx, X> Support<X> for Fx where
Fx: Deref,
<Fx as Deref>::Target: Support<X>,
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Fx: Deref,
<Fx as Deref>::Target: Support<X>,
impl<T> ToOwned for T where
T: Clone,
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T: Clone,
type Owned = T
The resulting type after obtaining ownership.
fn to_owned(&self) -> T
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fn clone_into(&self, target: &mut T)
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impl<T> ToString for T where
T: Display + ?Sized,
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T: Display + ?Sized,
impl<T, U> TryFrom<U> for T where
U: Into<T>,
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U: Into<T>,
type Error = Infallible
The type returned in the event of a conversion error.
fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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impl<T, U> TryInto<U> for T where
U: TryFrom<T>,
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U: TryFrom<T>,
type Error = <U as TryFrom<T>>::Error
The type returned in the event of a conversion error.
fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>
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impl<V, T> VZip<V> for T where
V: MultiLane<T>,
V: MultiLane<T>,
fn vzip(self) -> V
impl<Fx, X> Variance<X> for Fx where
Fx: Deref,
<Fx as Deref>::Target: Variance<X>,
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Fx: Deref,
<Fx as Deref>::Target: Variance<X>,