/**
 * Options for kernel density estimation
 */
export interface KDEOptions {
    /** Bandwidth parameter (if omitted, uses Silverman's rule) */
    bandwidth?: number;
    /** Number of x positions to sample */
    samples?: number;
    /** Kernel function type */
    kernel?: 'gaussian';
}
/**
 * Calculates bandwidth using Silverman's rule of thumb
 * @param values - Array of data values
 * @returns Calculated bandwidth
 */
export declare function silvermanBandwidth(values: number[]): number;
/**
 * Performs kernel density estimation on a dataset
 * @param values - Array of data values
 * @param domain - Range to evaluate the density over [min, max]
 * @param opts - KDE options
 * @returns Array of {x, y} density curve points
 */
export declare function kde(values: number[], domain: [number, number], opts?: KDEOptions): {
    x: number;
    y: number;
}[];
/**
 * Normalizes density values to 0-1 range
 * @param points - Array of density curve points
 * @returns Normalized points
 */
export declare function normalizeDensity(points: {
    x: number;
    y: number;
}[]): {
    x: number;
    y: number;
}[];