Struct sim::output_analysis::IndependentSample [−][src]
pub struct IndependentSample<T> { /* fields omitted */ }
Expand description
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
This constructor method creates an IndependentSample
from a vector
of floating point values.
pub fn confidence_interval_mean(
&self,
alpha: T
) -> Result<ConfidenceInterval<T>, SimulationError>
pub fn confidence_interval_mean(
&self,
alpha: T
) -> Result<ConfidenceInterval<T>, SimulationError>
Calculate the confidence interval of the mean, base on the provided value of alpha.
Return the sample mean.
Trait Implementations
Returns the “default value” for a type. Read more
fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
Deserialize this value from the given Serde deserializer. Read more
Auto Trait Implementations
impl<T> RefUnwindSafe for IndependentSample<T> where
T: RefUnwindSafe,
impl<T> Send for IndependentSample<T> where
T: Send,
impl<T> Sync for IndependentSample<T> where
T: Sync,
impl<T> Unpin for IndependentSample<T> where
T: Unpin,
impl<T> UnwindSafe for IndependentSample<T> where
T: UnwindSafe,
Blanket Implementations
Mutably borrows from an owned value. Read more
pub fn vzip(self) -> V