Struct RandomVariable 

pub struct RandomVariable {
    pub variable: Vec<f64>,
    pub probability: Vec<f64>,
}

Represents a univariate discrete Random Variable containing mapped outcomes and matching probability mass profiles.

Struct Elements

• variable: Contiguous storage tracking distinct numeric real outcomes ($X$).
• probability: Matching distribution array tracking distinct weights or probability mass parameters ($P(X)$).

Fields

variable: Vec<f64>

probability: Vec<f64>

Implementations

impl RandomVariable

pub fn new(x: Vec<f64>, px: Vec<f64>) -> Self

Instantiates a new entry tracking outcomes and matching process weights.

pub fn mean(&self) -> CDHResult<f64>

Computes the true expectation parameter mean ($E[X]$) of the random process.

$$E[X] = \sum x_i p(x_i)$$

Example

let rv = RandomVariable::new(vec![1.0, 2.0], vec![0.5, 0.5]);
assert_eq!(rv.mean().unwrap(), 1.5);

pub fn variance(&self) -> CDHResult<f64>

Computes the exact variance ($\text{Var}(X)$) using structural deviations to counter float degradation noise.

$$\text{Var}(X) = E[(X - \mu)^2] = \sum (x_i - \mu)^2 p(x_i)$$

pub fn expectation_from_func<H>(&self, h: H) -> CDHResult<f64>

where H: Fn(f64) -> f64,

Transforms elements via an arbitrary closure parameter and sums the targeted transformation grid weights.

$$E[h(X)] = \sum h(x_i) p(x_i)$$

pub fn expectation_from_set(&self, hx: &[f64]) -> CDHResult<f64>

Evaluates the functional expectation cross product against an isolated reference sequence slice.

pub fn std_deviation(&self) -> CDHResult<f64>

Computes the standard deviation ($\sigma$) of the isolated distribution.

pub fn moment_generating_func(&self, t: f64) -> CDHResult<f64>

Generates the Moment Generating Function evaluation value ($M_X(t)$) using precise hardware-level scaling exponents.

$$M_X(t) = E[e^{tX}]$$

pub fn characteristic_func(&self, t: f64) -> CDHResult<f64>

👎Deprecated since 0.1.0: Returns Err. f64 cannot represent complex numbers required for E[e^(itX)]. Will be implemented when complex number support is added.

Deprecated method indicating complex real-space value tracking limits.

Errors

Always returns an Err variant because complex number tracks require imaginary extensions not native to f64.

pub fn variance_operator<H>(&self, h: H) -> CDHResult<f64>

where H: Clone + Fn(f64) -> f64,

Calculates dispersion changes over custom functional projections while protecting closure scopes.

Trait Implementations

impl Clone for RandomVariable

fn clone(&self) -> RandomVariable

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for RandomVariable

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

Formats the value using the given formatter.