pub fn calculate_critical_value(n1: usize, n2: usize, confidence: f64) -> Result<f64, TestError> {
    if confidence.is_nan() || !(0.0 < confidence && confidence < 1.0) {
        return Err(TestError::ConfidenceMustBeBetweenZeroAndOneExclusive);
    }

    // Only supports samples of size > 7.
    if n1 < 8 || n2 < 8 {
        return Err(TestError::SequenceHasFewerThanEightElements);
    }

    // The test statistic is between zero and one so can binary search quickly
    // for the critical value.
    let mut low = 0.0;
    let mut high = 1.0;

    for _ in 1..200 {
        if low + 1e-8 >= high {
            return Ok(high);
        }

        let mid = low + (high - low) / 2.0;
        let reject_probability = calculate_reject_probability(mid, n1, n2)?;

        if reject_probability > confidence {
            // Maintain invariant that reject_probability(high) > confidence.
            high = mid;
        } else {
            // Maintain invariant that reject_probability(low) <= confidence.
            low = mid;
        }
    }
    Err(TestError::CouldNotConvergeOnCriticalValue {
        sample_size_1: n1,
        sample_size_2: n2,
        confidence,
    })
}
/// Calculate the critical value for the two sample Kolmogorov-Smirnov test.
///
///
/// No convergence error returned if the binary search does not locate the critical
/// value in less than 200 iterations.
///
/// # Examples
///
/// ```
/// extern crate kolmogorov_smirnov as ks;
///
/// let critical_value = ks::calculate_critical_value(256, 256, 0.95).unwrap();
/// println!("Critical value at 95% confidence for samples of size 256 is {}",
///       critical_value);
/// ```
Calculate the critical value for the two sample Kolmogorov-Smirnov test.
No convergence error returned if the binary search does not locate the critical
value in less than 200 iterations.
Calculate the critical value for the two sample Kolmogorov - Smirnov test . No convergence error returned if the binary search does not locate the critical value in less than 200 iterations .
pub fn calculate_critical_value(n1: usize, n2: usize, confidence: f64) -> Result<f64, TestError> {
    if confidence.is_nan() || !(0.0 < confidence && confidence < 1.0) {
        return Err(TestError::ConfidenceMustBeBetweenZeroAndOneExclusive);
    }
    // Only supports samples of size > 7.
    if n1 < 8 || n2 < 8 {
        return Err(TestError::SequenceHasFewerThanEightElements);
    }
    // The test statistic is between zero and one so can binary search quickly
    // for the critical value.
    let mut low = 0.0;
    let mut high = 1.0;
    for _ in 1..200 {
        if low + 1e-8 >= high {
            return Ok(high);
        }
        let mid = low + (high - low) / 2.0;
        let reject_probability = calculate_reject_probability(mid, n1, n2)?;
        if reject_probability > confidence {
            // Maintain invariant that reject_probability(high) > confidence.
            high = mid;
        } else {
            // Maintain invariant that reject_probability(low) <= confidence.
            low = mid;
        }
    }
    Err(TestError::CouldNotConvergeOnCriticalValue {
        sample_size_1: n1,
        sample_size_2: n2,
        confidence,
    })
}
pub fn calculate_critical_value ( n1 : usize , n2 : usize , confidence : f64 ) -> Result < f64 , TestError > { if confidence . is_nan ( ) || ! ( 0.0 < confidence && confidence < 1.0 ) { return Err ( TestError :: ConfidenceMustBeBetweenZeroAndOneExclusive ) ; } // Only supports samples of size > 7. if n1 < 8 || n2 < 8 { return Err ( TestError :: SequenceHasFewerThanEightElements ) ; } // The test statistic is between zero and one so can binary search quickly // for the critical value. let mut low = 0.0 ; let mut high = 1.0 ; for _ in 1 .. 200 { if low + 1e-8 >= high { return Ok ( high ) ; } let mid = low + ( high - low ) / 2.0 ; let reject_probability = calculate_reject_probability ( mid , n1 , n2 ) ? ; if reject_probability > confidence { // Maintain invariant that reject_probability(high) > confidence. high = mid ; } else { // Maintain invariant that reject_probability(low) <= confidence. low = mid ; } } Err ( TestError :: CouldNotConvergeOnCriticalValue { sample_size_1 : n1 , sample_size_2 : n2 , confidence , } ) }
Calculate the critical value for the two sample Kolmogorov-Smirnov test.
Calculate the critical value for the two sample Kolmogorov - Smirnov test .
n1
usize
n2
usize
confidence
f64
n1
usize
n2
usize
confidence
f64
examples
```
extern crate kolmogorov_smirnov as ks.

let critical_value = ks::calculate_critical_value(256, 256, 0.95).unwrap();
println!("Critical value at 95% confidence for samples of size 256 is {}",
critical_value);
```
` ` ` extern crate kolmogorov_smirnov as ks . let critical_value = ks :: calculate_critical_value ( 256 256 0 . 95 ) . unwrap () ; println! ( " Critical value at 95% confidence for samples of size 256 is {} " critical_value ) ; ` ` `