Struct InvGamma 

pub struct InvGamma { /* private fields */ }

Inverse gamma distribution IG(α, β) over x in (0, ∞).

            β^α
f(x|α, β) = ----  x^(-α-1) e^(-β/x)
            Γ(α)

Implementations

impl InvGamma

pub fn new(shape: f64, scale: f64) -> Result<Self, InvGammaError>

Create a new Gamma distribution with shape (α) and rate (β).

Arguments

• shape: shape parameter, α
• scale scale parameter, β

pub fn new_unchecked(shape: f64, scale: f64) -> Self

Creates a new InvGamma without checking whether the parameters are valid.

pub fn shape(&self) -> f64

Get the shape parameter

Example

let ig = InvGamma::new(1.0, 2.0).unwrap();
assert_eq!(ig.shape(), 1.0);

pub fn set_shape(&mut self, shape: f64) -> Result<(), InvGammaError>

Set the shape parameter

Example

let mut ig = InvGamma::new(2.0, 1.0).unwrap();
assert_eq!(ig.shape(), 2.0);

ig.set_shape(1.1).unwrap();
assert_eq!(ig.shape(), 1.1);

Will error for invalid values

assert!(ig.set_shape(1.1).is_ok());
assert!(ig.set_shape(0.0).is_err());
assert!(ig.set_shape(-1.0).is_err());
assert!(ig.set_shape(f64::INFINITY).is_err());
assert!(ig.set_shape(f64::NEG_INFINITY).is_err());
assert!(ig.set_shape(f64::NAN).is_err());

pub fn set_shape_unchecked(&mut self, shape: f64)

Set the shape parameter without input validation

pub fn scale(&self) -> f64

Get the scale parameter

Example

let ig = InvGamma::new(1.0, 2.0).unwrap();
assert_eq!(ig.scale(), 2.0);

pub fn set_scale(&mut self, scale: f64) -> Result<(), InvGammaError>

Set the scale parameter

Example

let mut ig = InvGamma::new(2.0, 1.0).unwrap();
assert_eq!(ig.scale(), 1.0);

ig.set_scale(1.1).unwrap();
assert_eq!(ig.scale(), 1.1);

Will error for invalid values

assert!(ig.set_scale(1.1).is_ok());
assert!(ig.set_scale(0.0).is_err());
assert!(ig.set_scale(-1.0).is_err());
assert!(ig.set_scale(f64::INFINITY).is_err());
assert!(ig.set_scale(f64::NEG_INFINITY).is_err());
assert!(ig.set_scale(f64::NAN).is_err());

pub fn set_scale_unchecked(&mut self, scale: f64)

Set the scale parameter without input validation

Trait Implementations

impl Cdf<f32> for InvGamma

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 InvGamma

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 Clone for InvGamma

fn clone(&self) -> InvGamma

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl ContinuousDistr<f32> for InvGamma

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 InvGamma

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 Debug for InvGamma

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

Formats the value using the given formatter.

impl Default for InvGamma

fn default() -> Self

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for InvGamma

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for InvGamma

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

Formats the value using the given formatter.

impl Entropy for InvGamma

fn entropy(&self) -> f64

The entropy, H(X)

impl From<&InvGamma> for String

fn from(invgam: &InvGamma) -> String

Converts to this type from the input type.

impl HasDensity<f32> for InvGamma

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

Probability function

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

Probability function

impl HasDensity<f64> for InvGamma

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

Probability function

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

Probability function

impl HasSuffStat<f32> for InvGamma

type Stat = InvGammaSuffStat

fn empty_suffstat(&self) -> Self::Stat

fn ln_f_stat(&self, stat: &Self::Stat) -> f64

Return the log likelihood for the data represented by the sufficient statistic.

impl HasSuffStat<f64> for InvGamma

type Stat = InvGammaSuffStat

fn empty_suffstat(&self) -> Self::Stat

fn ln_f_stat(&self, stat: &Self::Stat) -> f64

Return the log likelihood for the data represented by the sufficient statistic.

impl Kurtosis for InvGamma

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

impl Mean<f32> for InvGamma

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

Returns None if the mean is undefined

impl Mean<f64> for InvGamma

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

Returns None if the mean is undefined

impl Mode<f32> for InvGamma

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

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

impl Mode<f64> for InvGamma

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

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

impl Parameterized for InvGamma

type Parameters = InvGammaParameters

fn emit_params(&self) -> Self::Parameters

fn from_params(params: Self::Parameters) -> Self

fn map_params(&self, f: impl Fn(Self::Parameters) -> Self::Parameters) -> Self

impl PartialEq for InvGamma

fn eq(&self, other: &InvGamma) -> 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 Sampleable<f32> for InvGamma

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 sample_stream<'r, R: Rng>( &'r self, rng: &'r mut R, ) -> Box<dyn Iterator<Item = X> + 'r>

Create a never-ending iterator of samples

impl Sampleable<f64> for InvGamma

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 sample_stream<'r, R: Rng>( &'r self, rng: &'r mut R, ) -> Box<dyn Iterator<Item = X> + 'r>

Create a never-ending iterator of samples

impl Scalable for InvGamma

type Output = InvGamma

type Error = InvGammaError

fn scaled(self, scale: f64) -> Result<Self::Output, Self::Error>

where Self: Sized,

fn scaled_unchecked(self, scale: f64) -> Self::Output

where Self: Sized,

impl Serialize for InvGamma

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Shiftable for InvGamma

type Output = Shifted<InvGamma>

type Error = ShiftedError

fn shifted(self, shift: f64) -> Result<Self::Output, Self::Error>

where Self: Sized,

fn shifted_unchecked(self, shift: f64) -> Self::Output

where Self: Sized,

impl Skewness for InvGamma

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

impl Support<f32> for InvGamma

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

Returns true if x is in the support of the Rv

impl Support<f64> for InvGamma

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

Returns true if x is in the support of the Rv

impl Variance<f64> for InvGamma

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

Returns None if the variance is undefined

impl StructuralPartialEq for InvGamma