import { RegressorBase } from '../base';
import { Params } from '../base/estimator';
export type GLMLink = 'auto' | 'identity' | 'log';
export interface TweedieRegressorProps {
    power?: number;
    alpha?: number;
    fitIntercept?: boolean;
    link?: GLMLink;
    maxIter?: number;
    tol?: number;
}
declare class BaseGLM extends RegressorBase {
    protected power: number;
    protected regularization: number;
    protected fitIntercept: boolean;
    protected link: GLMLink;
    protected maxIter: number;
    protected tol: number;
    protected coefState: number[];
    protected interceptState: number;
    protected nIterState: number;
    constructor(props: TweedieRegressorProps);
    getParams(): Params;
    private activeLink;
    private mean;
    private loss;
    fit(X: number[][], y: number[]): void;
    predict(X: number[][]): number[];
    get coef(): number[];
    get intercept(): number;
    get nIter(): number;
}
export declare class TweedieRegressor extends BaseGLM {
    constructor(props?: TweedieRegressorProps);
}
export interface PoissonRegressorProps extends Omit<TweedieRegressorProps, 'power' | 'link'> {
}
export declare class PoissonRegressor extends BaseGLM {
    constructor(props?: PoissonRegressorProps);
    getParams(): Params;
}
export interface GammaRegressorProps extends Omit<TweedieRegressorProps, 'power' | 'link'> {
}
export declare class GammaRegressor extends BaseGLM {
    constructor(props?: GammaRegressorProps);
    getParams(): Params;
}
export {};