[−][src]Type Definition rstat::multivariate::normal::IsotropicNormal
type IsotropicNormal = Normal<f64>;
Methods
impl IsotropicNormal[src]
pub fn isotropic(mu: Array1<f64>, sigma: f64) -> Result<Self, Error>[src]
pub fn isotropic_unchecked(mu: Array1<f64>, sigma: f64) -> Self[src]
pub fn homogeneous(n: usize, mu: f64, sigma: f64) -> Result<Self, Error>[src]
pub fn homogenous_unchecked(n: usize, mu: f64, sigma: f64) -> Self[src]
pub fn standard(n: usize) -> Result<Self, Error>[src]
pub fn standard_unchecked(n: usize) -> Self[src]
pub fn precision(&self) -> f64[src]
pub fn z(&self, x: &[f64]) -> f64[src]
Trait Implementations
impl ContinuousDistribution for IsotropicNormal[src]
impl Distribution for IsotropicNormal[src]
type Support = ProductSpace<Reals>
Support of sample elements.
type Params = Params<f64>
Parameter set uniquely defining the instance.
fn support(&self) -> ProductSpace<Reals>[src]
fn params(&self) -> Self::Params[src]
fn cdf(&self, _: &Vec<f64>) -> Probability[src]
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Vec<f64>[src]
fn into_support(self) -> Self::Support[src]
fn into_params(self) -> Self::Params[src]
fn ccdf(&self, x: &Sample<Self>) -> Probability[src]
fn log_cdf(&self, x: &Sample<Self>) -> f64[src]
fn log_ccdf(&self, x: &Sample<Self>) -> f64[src]
fn sample_n<R: Rng + ?Sized>(&self, rng: &mut R, n: usize) -> Vec<Sample<Self>>[src]
fn sample_iter<'a, R: Rng + ?Sized>(
&'a self,
rng: &'a mut R
) -> Sampler<'a, Self, R>[src]
&'a self,
rng: &'a mut R
) -> Sampler<'a, Self, R>