Struct ExponentialDistribution

pub struct ExponentialDistribution { /* private fields */ }

Exponential distribution with an optional shift. The probability density function (PDF) is defined as follows:

For a positive tail (when positive_tail is true):

f(x; λ, offset) = λ exp(-λ (x - offset)) for x ≥ offset

For a negative tail (when positive_tail is false):

f(x; λ, offset) = λ exp(-λ (offset - x)) for x ≤ offset

In both cases, the PDF is 0 outside the specified domain.

For more information, see:

https://en.wikipedia.org/wiki/Exponential_distribution

Implementations

impl ExponentialDistribution

pub fn data_type(&self) -> DataType

pub fn rate(&self) -> &ScalarValue

pub fn offset(&self) -> &ScalarValue

pub fn positive_tail(&self) -> bool

pub fn mean(&self) -> Result<ScalarValue, DataFusionError>

pub fn median(&self) -> Result<ScalarValue, DataFusionError>

pub fn variance(&self) -> Result<ScalarValue, DataFusionError>

pub fn range(&self) -> Result<Interval, DataFusionError>

Trait Implementations

impl Clone for ExponentialDistribution

fn clone(&self) -> ExponentialDistribution

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for ExponentialDistribution

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl PartialEq for ExponentialDistribution

fn eq(&self, other: &ExponentialDistribution) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for ExponentialDistribution