Trait Statistics

pub trait Statistics<T> {
    // Required methods
    fn mean(&self) -> Option<T>;
    fn var(&self) -> Option<T>;
    fn stddev(&self) -> Option<T>;
    fn median(&self) -> Option<T>;
    fn quantile(&self, q: T) -> Option<T>;
    fn iqr(&self) -> Option<T>;
    fn min(&self) -> Option<T>;
    fn max(&self) -> Option<T>;
    fn cumsum(&self) -> Vector<T>;
}

Trait definition for Statistics, generic over type T. T is expected to be a floating-point type like f32 or f64.

Required Methods

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

Computes the mean (average) of the data. Returns an Option where None represents an empty dataset.

fn var(&self) -> Option<T>

Computes the variance of the data. Returns an Option, where None represents an empty dataset. Variance is the average of the squared deviations from the mean.

fn stddev(&self) -> Option<T>

Computes the standard deviation of the data. Returns an Option, where None represents an empty dataset. Standard deviation is the square root of the variance.

fn median(&self) -> Option<T>

Computes the median of the data. Returns an Option, where None represents an empty dataset. The median is the value separating the higher half from the lower half.

fn quantile(&self, q: T) -> Option<T>

Computes the quantile for the given fraction q. q is expected to be a floating-point value between 0 and 1. Returns an Option where None represents an empty dataset. For example, q = 0.5 gives the median, q = 0.25 gives the 25th percentile.

fn iqr(&self) -> Option<T>

Computes the interquartile range (IQR) of the data. Returns an Option, where None represents an empty dataset. IQR is the range between the 25th percentile and 75th percentile.

fn min(&self) -> Option<T>

Returns the minimum value in the dataset, ignoring NaN values. Returns an Option, where None represents an empty dataset.

fn max(&self) -> Option<T>

Returns the maximum value in the dataset, ignoring NaN values. Returns an Option, where None represents an empty dataset.

fn cumsum(&self) -> Vector<T>

Computes the cumulative sum of the data. Returns a Vector<T>, where each element is the cumulative sum up to that index. NaN values are ignored in the summation.

Implementors

impl<T> Statistics<T> for Vector<T>

where T: Float + ToPrimitive + Copy + PartialOrd,