/**
 * Typed Statistics Functions (Parallel-First)
 *
 * AssemblyScript-friendly TypeScript implementations with typed-function
 * integration and workerpool parallel execution.
 *
 * Following the parallel-first philosophy per CLAUDE.md:
 * - Use workers for ALL array transformations (Float64Array)
 * - Use workers for ALL numerical computations that can be batched
 * - Only fall back to sequential for trivial scalar operations
 *
 * @packageDocumentation
 */
/** 64-bit float (default for decimals) */
type f64 = number;
/** 32-bit signed integer */
type i32 = number;
/**
 * Normalization type for variance computation
 */
export type NormalizationType = 'unbiased' | 'uncorrected' | 'biased';
/**
 * Parallel sum with typed-function dispatch
 */
export declare const parallelStatSum: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel mean with typed-function dispatch
 */
export declare const parallelStatMean: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel variance with typed-function dispatch
 *
 * Uses Welford's algorithm for numerical stability
 */
export declare const parallelStatVariance: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel standard deviation with typed-function dispatch
 */
export declare const parallelStatStd: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel minimum with typed-function dispatch
 */
export declare const parallelStatMin: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel maximum with typed-function dispatch
 */
export declare const parallelStatMax: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel minmax with typed-function dispatch
 * Returns both min and max in a single pass
 */
export declare const parallelStatMinMax: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel median with typed-function dispatch
 *
 * Note: Median requires sorting which is O(n log n)
 */
export declare const parallelStatMedian: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel mode with typed-function dispatch
 * Returns the most frequently occurring value(s)
 */
export declare const parallelStatMode: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel product with typed-function dispatch
 */
export declare const parallelStatProd: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel Euclidean norm (L2 norm) with typed-function dispatch
 */
export declare const parallelStatNorm: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel Euclidean distance with typed-function dispatch
 */
export declare const parallelStatDistance: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel Pearson correlation coefficient
 */
export declare const parallelStatCorr: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel Mean Absolute Deviation
 */
export declare const parallelStatMAD: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel cumulative sum
 */
export declare const parallelStatCumsum: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Parallel quantile computation
 */
export declare const parallelStatQuantile: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Compute the p-th percentile of a Float64Array.
 *
 * Identical to `parallelStatQuantile(data, p / 100)`.
 * Uses WASM sort acceleration above WASM_SORT_THRESHOLD elements.
 *
 * @param data - Input data array.
 * @param p    - Percentile in [0, 100].
 */
export declare function parallelStatPercentile(data: Float64Array, p: f64): f64;
/**
 * Parallel histogram computation
 */
export declare const parallelStatHistogram: import("@danielsimonjr/mathts-core").TypedFunction;
/**
 * Select the k-th smallest element from an array using Hoare's quickselect algorithm.
 * Average O(n) time complexity.
 *
 * @param arr - Input array (not modified)
 * @param k - Zero-based index of the desired order statistic
 * @returns The k-th smallest element
 */
export declare function quickSelect(arr: number[], k: i32): f64;
/**
 * Find the median of an array in O(n) average time using quickselect.
 *
 * @param arr - Input array (not modified)
 * @returns The median value
 */
export declare function medianSelect(arr: number[]): f64;
/**
 * Find the k smallest elements from an array.
 *
 * @param arr - Input array (not modified)
 * @param k - Number of smallest elements to return
 * @returns Array of k smallest elements, sorted ascending
 */
export declare function minSelect(arr: number[], k: i32): number[];
/**
 * Find the k largest elements from an array.
 *
 * @param arr - Input array (not modified)
 * @param k - Number of largest elements to return
 * @returns Array of k largest elements, sorted descending
 */
export declare function maxSelect(arr: number[], k: i32): number[];
/**
 * Primary export: typed statistics functions
 */
export declare const typedStatistics: {
    sum: import("@danielsimonjr/mathts-core").TypedFunction;
    mean: import("@danielsimonjr/mathts-core").TypedFunction;
    variance: import("@danielsimonjr/mathts-core").TypedFunction;
    std: import("@danielsimonjr/mathts-core").TypedFunction;
    min: import("@danielsimonjr/mathts-core").TypedFunction;
    max: import("@danielsimonjr/mathts-core").TypedFunction;
    minMax: import("@danielsimonjr/mathts-core").TypedFunction;
    median: import("@danielsimonjr/mathts-core").TypedFunction;
    mode: import("@danielsimonjr/mathts-core").TypedFunction;
    prod: import("@danielsimonjr/mathts-core").TypedFunction;
    norm: import("@danielsimonjr/mathts-core").TypedFunction;
    distance: import("@danielsimonjr/mathts-core").TypedFunction;
    corr: import("@danielsimonjr/mathts-core").TypedFunction;
    mad: import("@danielsimonjr/mathts-core").TypedFunction;
    cumsum: import("@danielsimonjr/mathts-core").TypedFunction;
    quantile: import("@danielsimonjr/mathts-core").TypedFunction;
    percentile: typeof parallelStatPercentile;
    histogram: import("@danielsimonjr/mathts-core").TypedFunction;
    quickSelect: typeof quickSelect;
    medianSelect: typeof medianSelect;
    minSelect: typeof minSelect;
    maxSelect: typeof maxSelect;
};
/**
 * Initialize statistics processing pool
 */
export declare function initializeStatistics(): Promise<void>;
/**
 * Terminate statistics processing pool
 */
export declare function terminateStatistics(): Promise<void>;
export {};
//# sourceMappingURL=statistics.d.ts.map