Struct BasicMetrics 

pub struct BasicMetrics {
    pub mean: Decimal,
    pub median: Decimal,
    pub mode: Decimal,
    pub std_dev: Decimal,
}

Represents a collection of fundamental statistical metrics.

Overview

The BasicMetrics structure encapsulates the core descriptive statistics for a dataset, providing a quick summary of its central tendency, spread, and distribution properties. These metrics are widely used in statistical analysis, curve analysis, and various financial or scientific computations.

Fields

• mean - The arithmetic average of the dataset. Represents the central value where the sum of all data points is divided by the total number of points. Useful for understanding the overall trend or expected value of the dataset.

• median - The middle value in the dataset when sorted. If the dataset has an even number of elements, the median is the average of the two middle elements. A robust measure of central tendency, particularly in datasets with outliers.

• mode - The most frequently occurring value in the dataset. If no value repeats, the mode might not be well-defined (or may represent multi-modal distributions). Useful for identifying common or dominant values in a dataset.

• std_dev - The standard deviation of the dataset, which quantifies the amount of variation or dispersion from the mean. A key measure of data spread, often used for assessing volatility or risk in financial contexts.

Applications

The BasicMetrics structure is utilized in various domains requiring descriptive statistics:

• Financial Analysis:

  • Evaluate price variations, returns, and risks.

• Scientific Research:

  • Summarize observations and patterns in experimental data.

• Data Science:

  • Understand distributions, clean data, and preprocess datasets for machine learning models.

Integration

The BasicMetrics structure is often used as part of larger metric aggregations, such as:

• Metrics: Combines BasicMetrics with other metrics for a detailed analysis of curve behavior.
• AnalysisResult: Provides a high-level result of statistical and shape analysis for curves.

Remarks

• The values are expressed as Decimal to maintain precision, important in financial computations or datasets requiring high accuracy.
• The BasicMetrics structure is immutable and can be cloned/copied, making it efficient for use in concurrent or parallel computations.

Example Workflow

Typically, BasicMetrics is computed from a dataset using statistical functions and then integrated into a more comprehensive analysis pipeline.

Related Concepts

• ShapeMetrics: Captures shape-related properties like skewness and kurtosis.
• RiskMetrics: Measures risk characteristics of financial instruments.
• TrendMetrics: Represents time-based trends in data series.

Fields

mean: Decimal

The arithmetic mean (average) of the dataset. Calculated by summing all values and dividing by the count of values. Provides a measure of central tendency that is affected by all values, including outliers.

median: Decimal

The median value of the dataset. Represents the middle value when all data points are arranged in ascending order. For datasets with even count, it’s the average of the two middle values. Less sensitive to outliers than the mean.

mode: Decimal

The most frequently occurring value in the dataset. If multiple values occur with equal frequency, this typically represents the first encountered mode or a calculated central mode. For multi-modal distributions, this is a simplification.

std_dev: Decimal

The standard deviation of the dataset. Measures the amount of variation or dispersion from the mean. A low standard deviation indicates values tend to be close to the mean, while a high standard deviation indicates values are spread over a wider range.

Trait Implementations

impl Clone for BasicMetrics

fn clone(&self) -> Self

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl ComposeSchema for BasicMetrics

fn compose(generics: Vec<RefOr<Schema>>) -> RefOr<Schema>

impl Copy for BasicMetrics

impl Debug for BasicMetrics

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

Formats the value using the given formatter.

impl Display for BasicMetrics

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

Formats the value using the given formatter.

impl Serialize for BasicMetrics

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl ToSchema for BasicMetrics

fn name() -> Cow<'static, str>

Return name of the schema.

fn schemas(schemas: &mut Vec<(String, RefOr<Schema>)>)

Implement reference utoipa::openapi::schema::Schemas for this type.