Struct rstat::univariate::lognormal::LogNormal

pub struct LogNormal(_);

Methods

impl LogNormal

pub fn new(mu: f64, sigma: f64) -> Result<LogNormal, Error>

pub fn new_unchecked(mu: f64, sigma: f64) -> LogNormal

Trait Implementations

impl Clone for LogNormal

fn clone(&self) -> LogNormal

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl ContinuousDistribution for LogNormal

fn pdf(&self, x: &f64) -> f64

Evaluates the probability density function (PDF) at (x).

fn log_pdf(&self, x: &Sample<Self>) -> f64

Evaluates the log PDF at (x).

impl Copy for LogNormal

impl Debug for LogNormal

fn fmt(&self, f: &mut Formatter) -> Result

Formats the value using the given formatter.

impl Display for LogNormal

fn fmt(&self, f: &mut Formatter) -> Result

Formats the value using the given formatter.

impl Distribution for LogNormal

type Support = PositiveReals

Support of sample elements.

type Params = Params

Parameter set uniquely defining the instance.

fn support(&self) -> PositiveReals

Returns an instance of the support Space, Self::Support.

fn params(&self) -> Params

Returns an instance of Self::Params matching the parameters of self.

fn into_params(self) -> Params

fn cdf(&self, x: &f64) -> Probability

Evaluates the cumulative distribution function (CDF) at (x).

fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64

Draw a random value from the distribution support.

fn into_support(self) -> Self::Support

fn ccdf(&self, x: &Sample<Self>) -> Probability

Evaluates the complementary CDF at (x).

fn log_cdf(&self, x: &Sample<Self>) -> f64

Evaluates the log CDF at (x), i.e. (\ln{F(x)}).

fn log_ccdf(&self, x: &Sample<Self>) -> f64

Evaluates the log complementary CDF at (x), i.e. (\ln{(1 - F(x))}).

fn sample_n<R: Rng + ?Sized>(&self, rng: &mut R, n: usize) -> Vec<Sample<Self>>

Draw n random value from the distribution support.

fn sample_iter<'a, R: Rng + ?Sized>(
    &'a self,
    rng: &'a mut R
) -> Sampler<'a, Self, R>

Draw an indefinite number of random values from the distribution support.

impl Entropy for LogNormal

fn entropy(&self) -> f64

Computes the entropy value of the distribution, H(X).

impl FisherInformation for LogNormal

fn fisher_information(&self) -> Array2<f64>

Computes the Fisher information matrix of the distribution, I(X).

impl From<Normal> for LogNormal

fn from(normal: Normal) -> LogNormal

Performs the conversion.

impl From<Params> for LogNormal

fn from(params: Params) -> LogNormal

Performs the conversion.

impl Modes for LogNormal

fn modes(&self) -> Vec<f64>

Computes the mode(s) of the distribution.

impl Quantiles for LogNormal

fn quantile(&self, _: Probability) -> f64

Evaluates the inverse cumulative distribution function (CDF) at p.

fn median(&self) -> f64

Computes the median value of the distribution, Q(0.5).

fn cquantile(&self, p: Probability) -> f64

Evaluates the complementary quantile function at x: Q(1 - p).

fn lower_quartile(&self) -> f64

Computes the lower quartile of the distribution, Q(0.25).

fn upper_quartile(&self) -> f64

Computes the upper quartile of the distribution, Q(0.75).

fn iqr(&self) -> f64

Computes the interquartile range (IQR) of the distribution, Q(0.75) - Q(0.25).

fn lower_fence(&self) -> f64

Computes the lower fence of the distribution, Q(0.25) - 1.5 · IQR.

fn upper_fence(&self) -> f64

Computes the lower fence of the distribution, Q(0.75) + 1.5 · IQR.

impl UnivariateMoments for LogNormal

fn mean(&self) -> f64

Computes the expected value of the distribution.

fn variance(&self) -> f64

Computes the variance of the distribution.

fn skewness(&self) -> f64

Computes the skewness of the distribution.

fn excess_kurtosis(&self) -> f64

Computes the excess kurtosis of the distribution.

fn standard_deviation(&self) -> f64

Computes the standard deviation of the distribution.

fn kurtosis(&self) -> f64

Computes the kurtosis of the distribution.