type Vec = readonly number[] | Float64Array;
/**
 * Simple moving average over a trailing window of size `w`. Returns an array of
 * length `n − w + 1` (the "valid" convolution, like `numpy.convolve(..., 'valid')`).
 */
export declare function movingAverage(x: Vec, w: number): number[];
/**
 * Exponentially-weighted moving average with smoothing factor `alpha ∈ (0,1]`
 * (`yₜ = α·xₜ + (1−α)·yₜ₋₁`, seeded with `x₀`). Matches `pandas.ewm(alpha=…,
 * adjust=False).mean()`. Output has the same length as the input.
 */
export declare function ewma(x: Vec, alpha: number): number[];
/**
 * Remove a trend from `x`. `'linear'` (default) subtracts the least-squares line;
 * `'constant'` subtracts the mean. Matches `scipy.signal.detrend`.
 */
export declare function detrend(x: Vec, type?: 'linear' | 'constant'): number[];
/**
 * Autocorrelation function up to `nlags` (inclusive), biased estimator
 * (÷n, like `statsmodels.tsa.stattools.acf`). `acf[0] = 1`.
 */
export declare function acf(x: Vec, nlags: number): number[];
export {};
//# sourceMappingURL=timeseries-extra.d.ts.map