Struct rstat::univariate::degenerate::Degenerate

pub struct Degenerate<T: Zero + PartialOrd> {
    pub k: Loc<T>,
}

Fields

k: Loc<T>

Methods

impl<T: Zero + PartialOrd> Degenerate<T>

pub fn new(k: T) -> Degenerate<T>

Trait Implementations

impl<T: Clone + Zero + PartialOrd> Clone for Degenerate<T>

fn clone(&self) -> Degenerate<T>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl ContinuousDistribution for Degenerate<f64>

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<T: Debug + Zero + PartialOrd> Debug for Degenerate<T>

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

Formats the value using the given formatter.

impl<T: Zero + PartialOrd + Default> Default for Degenerate<T>

fn default() -> Degenerate<T>

Returns the "default value" for a type.

impl DiscreteDistribution for Degenerate<i64>

fn pmf(&self, x: &i64) -> Probability

Evaluates the probability mass function (PMF) at (x).

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

Evaluates the log PMF at (x).

impl<T: Zero + PartialOrd + Display> Display for Degenerate<T>

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

Formats the value using the given formatter.

impl Distribution for Degenerate<f64>

type Support = Reals

Support of sample elements.

type Params = Loc<f64>

Parameter set uniquely defining the instance.

fn support(&self) -> Reals

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

fn params(&self) -> Loc<f64>

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

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

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

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

Draw a random value from the distribution support.

fn into_support(self) -> Self::Support

fn into_params(self) -> Self::Params

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 Distribution for Degenerate<i64>

type Support = Integers

Support of sample elements.

type Params = Loc<i64>

Parameter set uniquely defining the instance.

fn support(&self) -> Integers

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

fn params(&self) -> Loc<i64>

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

fn cdf(&self, x: &i64) -> Probability

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

fn sample<R: Rng + ?Sized>(&self, _: &mut R) -> i64

Draw a random value from the distribution support.

fn into_support(self) -> Self::Support

fn into_params(self) -> Self::Params

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<T: Zero + PartialOrd> Entropy for Degenerate<T>

fn entropy(&self) -> f64

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

impl<T: Zero + PartialOrd> From<Loc<T>> for Degenerate<T>

fn from(loc: Loc<T>) -> Degenerate<T>

Performs the conversion.

impl Modes for Degenerate<f64>

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

Computes the mode(s) of the distribution.

impl Modes for Degenerate<i64>

fn modes(&self) -> Vec<i64>

Computes the mode(s) of the distribution.

impl Quantiles for Degenerate<f64>

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 Quantiles for Degenerate<i64>

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 Degenerate<f64>

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 kurtosis(&self) -> f64

Computes the kurtosis 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.

impl UnivariateMoments for Degenerate<i64>

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 kurtosis(&self) -> f64

Computes the kurtosis 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.