export declare function gaussianPDF(x: number, mu: number, sigma: number): number;
export declare function gaussianPDF(x: number[], mu: number, sigma: number): number[];
export declare function silvermanBandwidth(distances: number[], weights?: number[]): number;
export declare function kernelDensity(evalPoints: number[], samplePoints: number[], weights: number[], bandwidth: number): number[];
export interface CalibrateOptions {
    weights?: number[];
    method?: "auto" | "kde" | "gmm";
    bandwidthFactor?: number;
    densityPrior?: number[];
}
export interface CalibrateWithSampleOptions extends CalibrateOptions {
}
export interface GMMOptions {
    maxIter?: number;
    tol?: number;
    evalPoints?: number[];
}
export declare class VectorProbabilityTransform {
    readonly muG: number;
    readonly sigmaG: number;
    readonly baseRate: number | null;
    private readonly _logitBaseRate;
    constructor(muG: number, sigmaG: number, baseRate?: number | null);
    static fitBackground(distances: number[], options?: {
        baseRate?: number | null;
    }): VectorProbabilityTransform;
    _detectGap(distances: number[], thresholdRatio?: number): number | null;
    _gapWeights(distances: number[]): number[] | null;
    static sharpenWeights(weights: number[], temperature?: number): number[];
    static distanceDensityWeights(distances: number[]): number[];
    estimateKDE(distances: number[], weights: number[], bandwidthFactor?: number, options?: {
        evalPoints?: number[];
    }): number[];
    estimateGMM(distances: number[], weights?: number[] | null, options?: GMMOptions): number[];
    private static _signalMass;
    private _estimateRelevantDensity;
    logDensityRatio(distances: number, fRValues: number): number;
    logDensityRatio(distances: number[], fRValues: number[]): number[];
    calibrate(distances: number, options?: CalibrateOptions): number;
    calibrate(distances: number[], options?: CalibrateOptions): number[];
    calibrateWithSample(evalDistances: number, sampleDistances: number[], options?: CalibrateWithSampleOptions): number;
    calibrateWithSample(evalDistances: number[], sampleDistances: number[], options?: CalibrateWithSampleOptions): number[];
}
export declare function ivfDensityPrior(cellPopulation: number, avgPopulation: number, options?: {
    gamma?: number;
}): number;
export declare function ivfDensityPrior(cellPopulation: number[], avgPopulation: number, options?: {
    gamma?: number;
}): number[];
export declare function knnDensityPrior(kthDistance: number, globalMedianKth: number, options?: {
    gamma?: number;
}): number;
export declare function knnDensityPrior(kthDistance: number[], globalMedianKth: number, options?: {
    gamma?: number;
}): number[];
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