Struct rv::dist::LogNormal

pub struct LogNormal {
    pub mu: f64,
    pub sigma: f64,
}

LogNormal Distribution If x ~ Normal(μ, σ), then e^x ~ LogNormal(μ, σ).

Fields

mu: f64

log scale mean

sigma: f64

log scale standard deviation

Methods

impl LogNormal

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

pub fn standard() -> Self

Trait Implementations

impl Rv<f32> for LogNormal

fn ln_f(&self, x: &f32) -> f64

Probability function

fn draw<R: Rng>(&self, rng: &mut R) -> f32

Single draw from the Rv

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<f32>

Multiple draws of the Rv

fn f(&self, x: &X) -> f64

Probability function

impl Rv<f64> for LogNormal

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

Probability function

fn draw<R: Rng>(&self, rng: &mut R) -> f64

Single draw from the Rv

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<f64>

Multiple draws of the Rv

fn f(&self, x: &X) -> f64

Probability function

impl Support<f32> for LogNormal

fn supports(&self, x: &f32) -> bool

Returns true if x is in the support of the Rv

impl Support<f64> for LogNormal

fn supports(&self, x: &f64) -> bool

Returns true if x is in the support of the Rv

impl ContinuousDistr<f32> for LogNormal

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

The value of the Probability Density Function (PDF) at x

fn ln_pdf(&self, x: &X) -> f64

The value of the log Probability Density Function (PDF) at x

impl ContinuousDistr<f64> for LogNormal

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

The value of the Probability Density Function (PDF) at x

fn ln_pdf(&self, x: &X) -> f64

The value of the log Probability Density Function (PDF) at x

impl Cdf<f32> for LogNormal

fn cdf(&self, x: &f32) -> f64

The value of the Cumulative Density Function at x

fn sf(&self, x: &X) -> f64

Survival function, 1 - CDF(x)

impl Cdf<f64> for LogNormal

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

The value of the Cumulative Density Function at x

fn sf(&self, x: &X) -> f64

Survival function, 1 - CDF(x)

impl InverseCdf<f32> for LogNormal

fn invcdf(&self, p: f64) -> f32

The value of the x at the given probability in the CDF

fn quantile(&self, p: f64) -> X

Alias for invcdf

fn interval(&self, p: f64) -> (X, X)

Interval containing p proportion for the probability

impl InverseCdf<f64> for LogNormal

fn invcdf(&self, p: f64) -> f64

The value of the x at the given probability in the CDF

fn quantile(&self, p: f64) -> X

Alias for invcdf

fn interval(&self, p: f64) -> (X, X)

Interval containing p proportion for the probability

impl Mean<f32> for LogNormal

fn mean(&self) -> Option<f32>

Returns None if the mean is undefined

impl Mean<f64> for LogNormal

fn mean(&self) -> Option<f64>

Returns None if the mean is undefined

impl Median<f32> for LogNormal

fn median(&self) -> Option<f32>

Returns None if the median is undefined

impl Median<f64> for LogNormal

fn median(&self) -> Option<f64>

Returns None if the median is undefined

impl Mode<f32> for LogNormal

fn mode(&self) -> Option<f32>

Returns None if the mode is undefined or is not a single value

impl Mode<f64> for LogNormal

fn mode(&self) -> Option<f64>

Returns None if the mode is undefined or is not a single value

impl Variance<f64> for LogNormal

fn variance(&self) -> Option<f64>

Returns None if the variance is undefined

impl Entropy for LogNormal

fn entropy(&self) -> f64

The entropy, H(X)

impl Skewness for LogNormal

fn skewness(&self) -> Option<f64>

impl Kurtosis for LogNormal

fn kurtosis(&self) -> Option<f64>

impl<'_> From<&'_ LogNormal> for String

fn from(lognorm: &LogNormal) -> String

Performs the conversion.

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 Default for LogNormal

fn default() -> Self

Returns the "default value" for a type.

impl Display for LogNormal

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

Formats the value using the given formatter.

impl Debug for LogNormal

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

Formats the value using the given formatter.