Struct NegativeBinomial 

pub struct NegativeBinomial {
    pub r: f64,
    pub p: f64,
}

Negative Binomial distribution NegBinom(r, p).

Examples

use rs_stats::distributions::negative_binomial::NegativeBinomial;
use rs_stats::distributions::traits::DiscreteDistribution;

let nb = NegativeBinomial::new(5.0, 0.5).unwrap();
assert!((nb.mean() - 5.0).abs() < 1e-10);

Fields

r: f64

Number of successes r > 0 (can be non-integer, i.e. the overdispersion parameter)

p: f64

Success probability p ∈ (0, 1)

Implementations

impl NegativeBinomial

pub fn new(r: f64, p: f64) -> StatsResult<Self>

Creates a NegBinom(r, p) distribution.

pub fn fit(data: &[f64]) -> StatsResult<Self>

Method-of-moments fitting.

• mean = r(1−p)/p → p = mean/variance (requires variance > mean)
• r = mean² / (variance − mean)

Trait Implementations

impl Clone for NegativeBinomial

fn clone(&self) -> NegativeBinomial

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for NegativeBinomial

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for NegativeBinomial

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl DiscreteDistribution for NegativeBinomial

fn name(&self) -> &str

Human-readable distribution name.

fn num_params(&self) -> usize

Number of free parameters (used for AIC / BIC).

fn pmf(&self, k: u64) -> StatsResult<f64>

Probability mass function P(X = k).

fn logpmf(&self, k: u64) -> StatsResult<f64>

Natural logarithm of the PMF: ln P(X = k).

fn cdf(&self, k: u64) -> StatsResult<f64>

Cumulative distribution function P(X ≤ k).

fn mean(&self) -> f64

Mean (expected value) μ.

fn variance(&self) -> f64

Variance σ².

fn inverse_cdf(&self, p: f64) -> StatsResult<u64>

Quantile function: smallest k ≥ 0 such that CDF(k) ≥ p.

fn std_dev(&self) -> f64

Standard deviation σ = √(variance).

fn log_likelihood(&self, data: &[u64]) -> StatsResult<f64>

Sum of log-PMFs: Σ ln P(X = kᵢ).

fn aic(&self, data: &[u64]) -> StatsResult<f64>

AIC = 2k − 2·ln(L̂).

fn bic(&self, data: &[u64]) -> StatsResult<f64>

BIC = k·ln(n) − 2·ln(L̂).

impl Serialize for NegativeBinomial

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Copy for NegativeBinomial