[−][src]Trait changepoint::BocpdLike
Trait for implementors of Bayesian online change-point detection
Associated Types
type Fx: Rv<T>
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Type of type of distribution
type PosteriorPredictive: Rv<Self::Fx>
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Type of predictive prior distribution
Required methods
pub fn step(&mut self, value: &T) -> &[f64]
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Update the run-length detector and return a sequence of run length probabilities.
pub fn reset(&mut self)
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Reset internal state, new run-lengths will refer to steps after this point.
pub fn pp(&self) -> Self::PosteriorPredictive
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Generate the posterior predictive distribution
pub fn preload(&mut self, data: &[T])
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Preload a seqeunce into the default suff stat
Implementors
impl<K> BocpdLike<f64> for Argpcp<K> where
K: Kernel,
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K: Kernel,
type Fx = Gaussian
type PosteriorPredictive = NormalGamma
pub fn step(&mut self, value: &f64) -> &[f64]
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pub fn reset(&mut self)
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pub fn preload(&mut self, _data: &[f64])
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pub fn pp(&self) -> Self::PosteriorPredictive
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impl<X, Fx, Pr> BocpdLike<X> for Bocpd<X, Fx, Pr> where
Fx: Rv<X> + HasSuffStat<X>,
Pr: ConjugatePrior<X, Fx, Posterior = Pr> + Clone,
Fx::Stat: Clone,
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Fx: Rv<X> + HasSuffStat<X>,
Pr: ConjugatePrior<X, Fx, Posterior = Pr> + Clone,
Fx::Stat: Clone,
type Fx = Fx
type PosteriorPredictive = Mixture<Pr>
pub fn reset(&mut self)
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pub fn step(&mut self, data: &X) -> &[f64]
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Update the model with a new datum and return the distribution of run lengths.
pub fn pp(&self) -> Self::PosteriorPredictive
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pub fn preload(&mut self, data: &[X])
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impl<X, Fx, Pr> BocpdLike<X> for BocpdTruncated<X, Fx, Pr> where
Fx: Rv<X> + HasSuffStat<X>,
Pr: ConjugatePrior<X, Fx, Posterior = Pr> + Clone,
Fx::Stat: Clone,
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Fx: Rv<X> + HasSuffStat<X>,
Pr: ConjugatePrior<X, Fx, Posterior = Pr> + Clone,
Fx::Stat: Clone,