/**
 * ResultsAnalyzer — Post-process parameter sweep results.
 *
 * Computes summary statistics, sensitivity analysis, and Pareto fronts
 * from ExperimentOrchestrator output.
 */
import type { ExperimentResult, ExperimentRunResult } from './ExperimentOrchestrator';
export interface SweepSummary {
    /** Total runs */
    totalRuns: number;
    /** Runs that converged */
    convergedRuns: number;
    /** Best (minimum) objective value and its parameters */
    bestRun: ExperimentRunResult | null;
    /** Worst (maximum) objective value */
    worstRun: ExperimentRunResult | null;
    /** Mean objective value */
    meanObjective: number;
    /** Standard deviation of objective values */
    stdObjective: number;
    /** Total experiment wall-clock time */
    totalTimeMs: number;
}
export interface SensitivityResult {
    /** Parameter path */
    parameter: string;
    /** Correlation coefficient between parameter value and objective (-1 to 1) */
    correlation: number;
    /** Absolute correlation (measure of influence regardless of direction) */
    influence: number;
}
export interface ParetoPoint {
    /** Run index */
    index: number;
    /** Objective values [obj1, obj2, ...] */
    objectives: number[];
    /** Parameter overrides */
    overrides: Map<string, number>;
}
/**
 * Compute summary statistics for a sweep experiment.
 */
export declare function summarize(result: ExperimentResult): SweepSummary;
/**
 * Compute sensitivity of the objective to each swept parameter.
 * Uses Pearson correlation coefficient.
 */
export declare function sensitivity(result: ExperimentResult): SensitivityResult[];
/**
 * Compute 2D Pareto front (non-dominated solutions).
 * Minimizes both objectives.
 */
export declare function paretoFront(result: ExperimentResult, objective1: string, objective2: string): ParetoPoint[];
/**
 * Export sweep results as a CSV string.
 */
export declare function exportSweepCSV(result: ExperimentResult): string;
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