Struct russell_stat::DistributionLognormal

pub struct DistributionLognormal { /* private fields */ }

Defines the Lognormal distribution

Implementations

impl DistributionLognormal

pub fn new(mu_logx: f64, sig_logx: f64) -> Result<Self, StrError>

Creates a new Lognormal distribution

Input

• mu_logx – mean (μ) of log(x)
• sig_logx – standard deviation (σ) of log(x)

Examples found in repository

examples/distribution_lognormal.rs (line 6)

fn main() -> Result<(), StrError> {
    // generate samples
    let mut rng = rand::thread_rng();
    let dist = DistributionLognormal::new(0.0, 0.25)?;
    let nsamples = 10_000;
    let mut data = vec![0.0; nsamples];
    for i in 0..nsamples {
        data[i] = dist.sample(&mut rng);
    }
    println!("{}", statistics(&data));

    // text-plot
    let stations = (0..25).map(|i| (i as f64) * 0.1).collect::<Vec<f64>>();
    let mut hist = Histogram::new(&stations)?;
    hist.set_bar_char('✨').set_bar_max_len(30);
    hist.count(&data);
    println!("{:.2}", hist);
    Ok(())
}

pub fn new_from_mu_sig(mu: f64, sig: f64) -> Result<Self, StrError>

Creates a new Lognormal distribution given mean and standard deviation parameters

Input

• mu – mean μ
• sig – standard deviation σ

This function will hence calculate mu_logx (mean of log(x)) and sig_logx (std-dev of log(x))

Trait Implementations

impl ProbabilityDistribution for DistributionLognormal

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

Implements the Probability Density Function (CDF)

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

Implements the Cumulative Density Function (CDF)

fn mean(&self) -> f64

Returns the Mean

fn variance(&self) -> f64

Returns the Variance

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

Generates a pseudo-random number belonging to this probability distribution