Struct Stats 

pub struct Stats;

Implementations

impl Stats

pub fn mean(data: &[f64]) -> Option<f64>

pub fn median(data: &[f64]) -> Option<f64>

pub fn mode(data: &[f64]) -> Option<Vec<f64>>

pub fn variance(data: &[f64]) -> Option<f64>

pub fn std_dev(data: &[f64]) -> Option<f64>

pub fn range(data: &[f64]) -> Option<f64>

pub fn quartiles(data: &[f64]) -> Option<(f64, f64, f64)>

pub fn percentile(data: &[f64], p: f64) -> Option<f64>

pub fn skewness(data: &[f64]) -> Option<f64>

pub fn kurtosis(data: &[f64]) -> Option<f64>

pub fn covariance(x: &[f64], y: &[f64]) -> Option<f64>

pub fn correlation(x: &[f64], y: &[f64]) -> Option<f64>

pub fn z_scores(data: &[f64]) -> Option<Vec<f64>>

pub fn mad(data: &[f64]) -> Option<f64>

pub fn winsorized_mean(data: &[f64], trim: f64) -> Option<f64>

pub fn moving_average(data: &[f64], window: usize) -> Option<Vec<f64>>

pub fn exponential_smoothing(data: &[f64], alpha: f64) -> Option<Vec<f64>>

pub fn bonferroni_correction(p_values: &[f64]) -> Option<Vec<f64>>

pub fn benjamini_hochberg(p_values: &[f64]) -> Option<Vec<f64>>

pub fn kernel_density_estimation( data: &[f64], x: f64, bandwidth: f64, ) -> Option<f64>

pub fn bayesian_update( prior: f64, likelihood: f64, evidence: f64, ) -> Option<f64>

pub fn entropy(probabilities: &[f64]) -> Option<f64>

pub fn kullback_leibler_divergence(p: &[f64], q: &[f64]) -> Option<f64>

impl Stats

pub fn normal_pdf(x: f64, mean: f64, std_dev: f64) -> f64

pub fn cohens_d(data1: &[f64], data2: &[f64]) -> Option<f64>

pub fn linear_regression(x: &[f64], y: &[f64]) -> Option<(f64, f64)>

pub fn autocorrelation(data: &[f64], lag: usize) -> Option<f64>

pub fn binomial_pmf(k: u64, n: u64, p: f64) -> f64

Trait Implementations

impl Clone for Stats

fn clone(&self) -> Stats

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Stats

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

Formats the value using the given formatter.