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StatisticalCurve

optionstratlib_math::curves

Trait StatisticalCurve 

Source 
pub trait StatisticalCurve: MetricsExtractor {
    // Required method
    fn get_x_values(&self) -> Vec<Decimal>;

    // Provided methods
    fn generate_statistical_curve(
        &self,
        basic_metrics: &BasicMetrics,
        shape_metrics: &ShapeMetrics,
        range_metrics: &RangeMetrics,
        trend_metrics: &TrendMetrics,
        num_points: usize,
        seed: Option<u64>,
    ) -> Result<Curve, CurveError> { ... }
    fn generate_refined_statistical_curve(
        &self,
        basic_metrics: &BasicMetrics,
        shape_metrics: &ShapeMetrics,
        range_metrics: &RangeMetrics,
        trend_metrics: &TrendMetrics,
        num_points: usize,
        max_attempts: usize,
        tolerance: Decimal,
        seed: Option<u64>,
    ) -> Result<Curve, CurveError> { ... }
    fn verify_curve_metrics(
        &self,
        curve: &Curve,
        target_metrics: &BasicMetrics,
        tolerance: Decimal,
    ) -> Result<bool, CurveError> { ... }
}
Expand description

A trait for generating statistical curves based on metrics

This trait provides methods to generate curves that match specified statistical properties. It extends the MetricsExtractor trait to ensure implementing types can both extract and generate metrics.

Required Methods§

Source

fn get_x_values(&self) -> Vec<Decimal>

Retrieves the x-axis values for the statistical curve.

This method returns a vector of Decimal values representing the x-coordinates of the points that define the curve. These x-values are essential for plotting the curve and performing various statistical analyses.

§Returns

A Vec<Decimal> containing the x-values of the statistical curve. Each Decimal represents a point on the x-axis.

Provided Methods§

Source

fn generate_statistical_curve( &self, basic_metrics: &BasicMetrics, shape_metrics: &ShapeMetrics, range_metrics: &RangeMetrics, trend_metrics: &TrendMetrics, num_points: usize, seed: Option<u64>, ) -> Result<Curve, CurveError>

Generates a statistical curve with properties that match the provided metrics.

§Overview

This function creates a curve with statistical properties that approximate the specified metrics. It uses a combination of normal distribution sampling and transformations to achieve the desired statistical characteristics.

§Parameters
  • basic_metrics: Basic statistical properties like mean, median, mode, and standard deviation.
  • shape_metrics: Shape-related metrics like skewness and kurtosis.
  • range_metrics: Range information including min, max, and quartile data.
  • trend_metrics: Trend information including slope and intercept for linear trend.
  • num_points: Number of points to generate in the curve.
  • seed: Optional random seed for reproducible curve generation.
§Returns
  • Result<Curve, CurveError>: A curve matching the specified statistical properties, or an error if generation fails.
§Errors

Returns CurveError::ConstructionError when the requested combination of basic, shape and range-parameter metrics is infeasible (e.g. negative variance, inconsistent quantiles), and propagates CurveError::MetricsError when the per-sample metric evaluation fails.

Source

fn generate_refined_statistical_curve( &self, basic_metrics: &BasicMetrics, shape_metrics: &ShapeMetrics, range_metrics: &RangeMetrics, trend_metrics: &TrendMetrics, num_points: usize, max_attempts: usize, tolerance: Decimal, seed: Option<u64>, ) -> Result<Curve, CurveError>

Generates a refined statistical curve that iteratively adjusts to better match the target metrics.

This method extends the basic curve generation by performing multiple attempts with adjusted parameters until the resulting curve metrics are within the specified tolerance of the target metrics.

§Parameters
  • basic_metrics: Target basic statistical metrics
  • shape_metrics: Target shape metrics
  • range_metrics: Target range metrics
  • trend_metrics: Target trend metrics
  • num_points: Number of points to generate
  • max_attempts: Maximum number of generation attempts (default: 5)
  • tolerance: Acceptable difference between target and actual metrics (default: 0.1)
  • seed: Optional random seed for reproducibility
§Returns
  • Result<Curve, CurveError>: The generated curve or an error
§Errors

Same failure surface as StatisticalCurve::generate_statistical_curve, plus CurveError::ConstructionError when the refinement loop exhausts its iteration budget without matching the tolerance.

Source

fn verify_curve_metrics( &self, curve: &Curve, target_metrics: &BasicMetrics, tolerance: Decimal, ) -> Result<bool, CurveError>

Verifies if the metrics of the generated curve match the target metrics within the specified tolerance.

§Parameters
  • curve: The curve to verify
  • target_metrics: The target basic metrics to compare against
  • tolerance: Maximum acceptable difference between actual and target metrics
§Returns
  • Result<bool, CurveError>: True if metrics match within tolerance, false otherwise
§Errors

Propagates any CurveError::MetricsError or CurveError::ConstructionError raised while recomputing the curve’s actual metrics (typically when the curve contains non-finite samples or lacks the density required for the requested metric). Returns CurveError::AnalysisError when the gap between an actual and a target metric leaves the representable Decimal range.

Dyn Compatibility§

This trait is dyn compatible.

In older versions of Rust, dyn compatibility was called "object safety".

Implementors§