/**
 * Pure latency aggregation. Workers record raw samples; aggregation
 * happens once at report-build time, so the hot path stays cheap (no
 * histogram per sample). We use sort-based quantiles — adequate for
 * up to ~100k samples which covers light-load runs (10 workers × few
 * mins × 30 req/iter).
 *
 * For heavier load tests we would swap this for hdrhistogram-js, but
 * the design here ("軽量負荷") keeps the lightest possible
 * implementation.
 */
import type { LatencyStats } from "./types.js";
export declare function emptyLatencyStats(): LatencyStats;
/**
 * Compute basic latency statistics. Samples are NOT mutated.
 * Returns zeroed stats for an empty input.
 */
export declare function latencyStats(samplesMs: ReadonlyArray<number>): LatencyStats;
/**
 * Linear-interpolated quantile on a pre-sorted ascending array.
 * Matches numpy's "linear" interpolation.
 */
export declare function quantile(sortedAsc: ReadonlyArray<number>, q: number): number;
/** Parse `"5s"` / `"500ms"` / `"2m"` / number(ms) into a millisecond count. */
export declare function parseDurationMs(input: number | string): number;
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