@ai-on-browser/data-analysis-models
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Data analysis model package without any dependencies
40 lines (39 loc) • 1.29 kB
TypeScript
/**
* Markov switching
*/
export default class MarkovSwitching {
/**
* @param {number} regime Number of regime
*/
constructor(regime: number);
_regime: number;
_mu: any[];
_sigma: any[];
_stationary_prob(p: any): Matrix<number>;
_lh(x: any, mu: any, sigma: any): Matrix<T>;
_logL(x: any, mu: any, sigma: any, prob: any): number;
_prob(x: any): Matrix<T>[];
_nextParam(genProb: any, eps: any): any[];
_mcmc(x: any, eps: any, trial: any): (number[] | any[][] | Matrix<number>[])[];
_last_prob: Matrix<number>;
/**
* Fit model.
* @param {Array<Array<number>>} datas Training data
* @param {number} eps Parameter update range
* @param {number} trial Trial count
*/
fit(datas: Array<Array<number>>, eps: number, trial: number): void;
/**
* Returns probabilities.
* @param {Array<Array<number>>} datas Sample data
* @returns {Array<Array<number>>} Predicted values
*/
probability(datas: Array<Array<number>>): Array<Array<number>>;
/**
* Returns anomaly degrees.
* @param {Array<Array<number>>} datas Sample data
* @returns {number[]} Predicted values
*/
predict(datas: Array<Array<number>>): number[];
}
import Matrix from '../util/matrix.js';