/**
 * Partial autocorrelation function up to `nlags` (inclusive), via the
 * Levinson-Durbin recursion applied to the biased autocorrelations (`acf`).
 * `pacf[0] = 1`. Matches `statsmodels.tsa.stattools.pacf(x, nlags, method='ldb')`.
 *
 * @example
 * pacf([1, 2, 3, 2, 1, 2, 3, 2, 1, 2, 3, 2], 3) // => [1, 0, -0.8333..., 0]
 */
export declare function pacf(x: number[], nlags: number): number[];
/** Result of {@link ljungBox}. */
export interface LjungBoxResult {
    statistic: number;
    pValue: number;
}
/**
 * Ljung-Box portmanteau test for autocorrelation up to lag `lags`.
 * `Q = n(n+2) * Σ_{k=1}^{lags} ρ_k² / (n-k)`, `pValue = 1 - chiSquaredCDF(Q, lags)`.
 * Matches `statsmodels.stats.diagnostic.acorr_ljungbox`.
 */
export declare function ljungBox(x: number[], lags: number): LjungBoxResult;
/**
 * Durbin-Watson statistic for residual autocorrelation:
 * `Σ_{t=2}^{n}(e_t - e_{t-1})² / Σ_{t=1}^{n} e_t²`. Ranges (0, 4); ~2 indicates
 * no autocorrelation, <2 positive autocorrelation, >2 negative. Matches
 * `statsmodels.stats.stattools.durbin_watson`.
 */
export declare function durbinWatson(residuals: number[]): number;
/** Result of {@link adfuller}. */
export interface AdfullerResult {
    statistic: number;
    pValue: number;
    usedLag: number;
}
/**
 * Augmented Dickey-Fuller unit-root test (constant-only "c" model):
 * regresses `Δx_t` on `[1, x_{t-1}, Δx_{t-1}, ..., Δx_{t-maxlag}]` via OLS.
 * `statistic = coefficients[1] / stderr[1]` (the t-stat on the lagged level,
 * `coefficients[0]` being the intercept). `pValue` is an approximate
 * MacKinnon-style interpolation (see module docstring) — not exact.
 *
 * Default `maxlag = floor(12 * (n/100)^0.25)` (matches
 * `statsmodels.tsa.stattools.adfuller`'s default rule), clamped downward if
 * needed so the regression has more observations than parameters; `usedLag`
 * reports the lag count actually used.
 *
 * @example
 * adfuller(whiteNoiseSeries) // => { statistic: <very negative>, pValue: <small>, usedLag }
 */
export declare function adfuller(x: number[], maxlag?: number): AdfullerResult;
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