/**
 * Multivariate kernel density estimator
 */
export default class MultivariateKernelDensityEstimator {
    /**
     * @param {'silverman' | 'scott'} [method] Optimal bandwidth method
     */
    constructor(method?: "silverman" | "scott");
    _method: "scott" | "silverman";
    _kernel(invh: any, sqrtdeth: any, x: any): any;
    /**
     * Fit model.
     * @param {Array<Array<number>>} x Training data
     */
    fit(x: Array<Array<number>>): void;
    _x: Matrix<number[]>;
    _h: Matrix<number>;
    _invh: Matrix<number>;
    _hsqrtdet: number;
    /**
     * Returns probabilities of the datas.
     * @param {Array<Array<number>>} x Sample data
     * @returns {number[]} Predicted values
     */
    probability(x: Array<Array<number>>): number[];
    /**
     * Returns probabilities of the datas.
     * @param {Array<Array<number>>} x Sample data
     * @returns {number[]} Predicted values
     */
    predict(x: Array<Array<number>>): number[];
}
import Matrix from '../util/matrix.js';