/**
 * Median of `source` (ignores NaNs). Implemented via `quantile(source, 0.5)`.
 * @param source Input array
 * @returns Median value or NaN
 */
export declare function median(source: ArrayLike<number>): number;
/**
 * Compute the rolling median over a sliding window.
 * Ignores NaNs and validates `period`.
 * Returns a Float64Array with NaN entries for positions before the window fills.
 * @param source Input array
 * @param period Window length
 * @returns Float64Array of rolling medians
 */
export declare function rollmedian(source: ArrayLike<number>, period: number): Float64Array;
/**
 * Compute the quantile `q` of `source`, ignoring NaNs. Implements a
 * selection-based algorithm using quickselect for expected linear time.
 * @param source Input array
 * @param q Quantile in [0,1]
 * @returns Quantile value or NaN
 */
export declare function quantile(source: ArrayLike<number>, q: number): number;
/**
 * Compute multiple percentiles (quantiles) for `source`. When `qs.length`
 * is small, selection is used for each quantile; otherwise the data are
 * sorted once for efficiency.
 * @param source Input array
 * @param qs Array of quantiles in [0,1]
 * @returns Array of quantile values
 */
export declare function percentiles(source: ArrayLike<number>, qs: number[]): number[];
/**
 * Compute the rolling quantile over a sliding window.
 * Ignores NaNs and validates `period` and `q`.
 * Returns a Float64Array with NaN entries for positions before the window fills.
 * @param source Input array
 * @param period Window length
 * @param q Quantile in [0,1]
 * @returns Float64Array of rolling quantiles
 */
export declare function rollquantile(source: ArrayLike<number>, period: number, q: number): Float64Array;