/**
 * A random sampling of data in one and two dimensions with associated statistical tools.
 *
 * @since 1.0.0
 */
import * as RNEA from 'fp-ts/ReadonlyNonEmptyArray';
/**
 * A sample is a univariate collection of data
 *
 * @since 1.0.0
 * @category Model
 */
export declare type Sample = RNEA.ReadonlyNonEmptyArray<number>;
/**
 * A bivariate sample is a (free) sampling of two variables
 *
 * @since 1.0.0
 * @category Model
 */
export declare type BivariateSample = RNEA.ReadonlyNonEmptyArray<readonly [number, number]>;
/**
 * The average value over different variables
 *
 * @since 1.0.0
 * @category Statistics
 */
export declare const mean: (s: Sample) => number;
/**
 * The difference in observation from a mean of Sample
 *
 * @since 1.0.0
 * @category Statistics
 */
export declare const deviation: (s: Sample) => Sample;
/**
 * The covariance of a bivariate sample, is the mutual variance between the two random variables
 *
 * @since 1.0.0
 * @category Statistics
 */
export declare const covariance: (ab: BivariateSample) => number;
/**
 * The variance of a univariate sample
 *
 * @since 1.0.0
 * @category Statistics
 */
export declare const variance: (ab: Sample) => number;
/**
 * The correlation matrix where each index: i, j represent the correlation between those
 * two random variables
 *
 * @since 1.0.0
 * @category Statistics
 */
export declare const correlation: (ab: BivariateSample) => number;
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