[−][src]Type Definition rstat::multivariate::normal::IsotropicNormal
type IsotropicNormal = MvNormal<Vector<f64>, f64>;
Multivariate Normal distribution with mean \(\bm{\mu}\) and isotropic covariance matrix \(\sigma^2\bm{I}\).
Methods
impl IsotropicNormal
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pub fn isotropic<M: Into<Vector<f64>>>(
mu: M,
sigma2: f64
) -> Result<Self, Error>
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mu: M,
sigma2: f64
) -> Result<Self, Error>
Construct an \(n\)-dimensional IsotropicNormal distribution with mean \(\bm{\mu}\) and variance \(\sigma^2\bm{I}\).
Constraints
- The variance term is positive real.
Examples
let dist = IsotropicNormal::isotropic(vec![0.0, 1.0], 1.0); assert!(dist.is_ok());
pub fn isotropic_unchecked<M: Into<Vector<f64>>>(mu: M, sigma2: f64) -> Self
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Construct an \(n\)-dimensional IsotropicNormal distribution with mean \(\bm{\mu}\) and variance \(\sigma^2\bm{I}\), without checking for correctness.
Examples
let dist = IsotropicNormal::isotropic_unchecked(vec![0.0, 1.0], 1.0);
pub fn homogeneous(n: usize, mu: f64, sigma2: f64) -> Result<Self, Error>
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Construct an \(n\)-dimensional IsotropicNormal distribution with mean \(\mu\) and variance \(\sigma^2\) in each dimension.
Constraints
- The dimensionality is a positive integer.
Examples
let dist = IsotropicNormal::homogeneous(2, 0.0, 1.0); assert!(dist.is_ok());
pub fn homogeneous_unchecked(n: usize, mu: f64, sigma2: f64) -> Self
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Construct an \(n\)-dimensional IsotropicNormal distribution with mean \(\mu\) and variance \(\sigma^2\) in each dimension, without checking for correctness.
Examples
let dist = IsotropicNormal::homogeneous_unchecked(2, 0.0, 1.0);
pub fn standard(n: usize) -> Result<Self, Error>
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Construct an \(n\)-dimensional IsotropicNormal distribution with mean 0 and unit variance \(\sigma^2\) in each dimension.
Constraints
- The dimensionality is a positive integer.
Examples
let dist = IsotropicNormal::standard(2); assert!(dist.is_ok());
pub fn standard_unchecked(n: usize) -> Self
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Construct an \(n\)-dimensional IsotropicNormal distribution with mean 0 and unit variance \(\sigma^2\) in each dimension, without checking for correctness.
Examples
let dist = IsotropicNormal::standard_unchecked(2);
Trait Implementations
impl ContinuousDistribution for IsotropicNormal
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impl Distribution for IsotropicNormal
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type Support = ProductSpace<Reals>
Support of sample elements.
type Params = IsotropicNormalParams
Parameter set uniquely defining the instance.
fn support(&self) -> ProductSpace<Reals>
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fn params(&self) -> Self::Params
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fn cdf(&self, _: &Vec<f64>) -> Probability
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fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Vec<f64>
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fn into_support(self) -> Self::Support
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fn into_params(self) -> Self::Params
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fn ccdf(&self, x: &Sample<Self>) -> Probability
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fn log_cdf(&self, x: &Sample<Self>) -> f64
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fn log_ccdf(&self, x: &Sample<Self>) -> f64
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fn sample_n<R: Rng + ?Sized>(&self, rng: &mut R, n: usize) -> Vec<Sample<Self>>
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fn sample_iter<'a, R: Rng + ?Sized>(
&'a self,
rng: &'a mut R
) -> Sampler<'a, Self, R>
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&'a self,
rng: &'a mut R
) -> Sampler<'a, Self, R>