/**
 * Series convergence — detects whether a sequence of scalar measurements
 * is stabilizing, drifting, or noisy.
 *
 * Lifted from ADC convergence.ts. The per-turn `ConvergenceTracker` is
 * about progress *within* a single run; this module is about drift
 * *across* runs (e.g. "are my nightly eval scores stabilizing?").
 *
 * Three signals:
 *   - stabilized: last K values have low variance (< epsilon) — done
 *   - drifting:   recent trend is monotonic and beyond noise — regressing or improving
 *   - noisy:      neither — keep iterating, but flag as untrustworthy for gating
 */
export interface SeriesConvergenceOptions {
    /** Window size for "recent" analysis (default 5). */
    window?: number;
    /** Coefficient-of-variation threshold below which the window is stabilized (default 0.05 = 5%). */
    stableCv?: number;
    /** Minimum monotone run length to call drift (default 3). */
    driftRun?: number;
}
export interface SeriesConvergenceResult {
    state: 'stabilized' | 'drifting-up' | 'drifting-down' | 'noisy' | 'insufficient-data';
    windowMean: number;
    windowCv: number;
    /** Longest monotonic run at the tail of the series (positive for up, negative for down). */
    tailRun: number;
    /** True when n ≥ window AND windowCv ≤ stableCv. */
    stable: boolean;
}
export declare function analyzeSeries(values: number[], options?: SeriesConvergenceOptions): SeriesConvergenceResult;
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