Struct sim::output_analysis::IndependentSample

pub struct IndependentSample<T> { /* fields omitted */ }

The independent sample is for independent, identically-distributed (IID) samples, or where treating the data as an IID sample is determined to be reasonable. Typically, this will be non-time series data - no autocorrelation. There are no additional requirements on the data beyond being IID. For example, there are no normality assumptions. The TerminatingSimulationOutput or SteadyStateOutput structs are available for non-IID output analysis.

Implementations

impl<T: Float> IndependentSample<T>

pub fn post(points: Vec<T>) -> IndependentSample<T>

This constructor method creates an IndependentSample from a vector of floating point values.

pub fn confidence_interval_mean(&self, alpha: T) -> ConfidenceInterval<T>

Calculate the confidence interval of the mean, base on the provided value of alpha.

pub fn point_estimate_mean(&self) -> T

Return the sample mean.

pub fn variance(&self) -> T

Return the sample variance.

Trait Implementations

impl<T: Clone> Clone for IndependentSample<T>

fn clone(&self) -> IndependentSample<T>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<T: Debug> Debug for IndependentSample<T>

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

Formats the value using the given formatter.

impl<T: Default> Default for IndependentSample<T>

fn default() -> IndependentSample<T>

Returns the "default value" for a type.

impl<'de, T> Deserialize<'de> for IndependentSample<T> where
    T: Deserialize<'de>, 

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl<T> Serialize for IndependentSample<T> where
    T: Serialize, 

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

Serialize this value into the given Serde serializer.