lakutata/src/lib/helpers/Statistics.mjs

An IoC-based universal application framework.

import { e as t, m as a, a as s, s as r, q as e, p as i, b as n, c, d as u, f as o, h as m, g as l, r as p, i as d, v as b, j as g, k as v, l as h, n as S, o as k, t as M, z as R, u as f, w as q, x as D, y as P, A as T, B as x, C as A, D as w, E as L, F as V, G as j, H as y, I as F, J as O, K as z, L as C, M as E, N, O as W, P as B, Q as G, R as H, S as I, T as J, U as K, V as Q, W as U, X, Y, Z, _ as $, $ as _, a0 as tt } from "../../../vendor/Package.16.mjs";

class Statistics {
    static {
        this.epsilon = t;
    }
    static min(t) {
        return a(t);
    }
    static max(t) {
        return s(t);
    }
    static sum(t) {
        return r(t);
    }
    static quantile(t, a) {
        return e(t, a);
    }
    static product(t) {
        return i(t);
    }
    static mean(t) {
        return n(t);
    }
    static average(t) {
        return n(t);
    }
    static addToMean(t, a, s) {
        return c(t, a, s);
    }
    static addToAverage(t, a, s) {
        return c(t, a, s);
    }
    static mode(t) {
        return u(t);
    }
    static median(t) {
        return o(t);
    }
    static harmonicMean(t) {
        return m(t);
    }
    static geometricMean(t) {
        return l(t);
    }
    static rootMeanSquare(t) {
        return p(t);
    }
    static sampleSkewness(t) {
        return d(t);
    }
    static variance(t) {
        return b(t);
    }
    static sampleVariance(t) {
        return g(t);
    }
    static standardDeviation(t) {
        return v(t);
    }
    static sampleStandardDeviation(t) {
        return h(t);
    }
    static medianAbsoluteDeviation(t) {
        return S(t);
    }
    static interquartileRange(t) {
        return k(t);
    }
    static sumNthPowerDeviations(t, a) {
        return M(t, a);
    }
    static zScore(t, a, s) {
        return R(t, a, s);
    }
    static correlation(t, a) {
        return f(t, a);
    }
    static sampleCovariance(t, a) {
        return q(t, a);
    }
    static rSquared(t) {
        return D(t, this.linearRegressionLine(this.linearRegression(t)));
    }
    static linearRegression(t) {
        return P(t);
    }
    static linearRegressionLine(t) {
        return T(t);
    }
    static shuffle(t) {
        return x(t);
    }
    static sampleWithReplacement(t, a) {
        return A(t, a);
    }
    static sample(t, a) {
        return w(t, a, Math.random);
    }
    static randomPickOne(t) {
        return this.sample(t, 1)[0];
    }
    static randomPickMany(t, a) {
        return this.sample(t, a);
    }
    static bernoulliDistribution(t) {
        return L(t);
    }
    static binomialDistribution(t, a) {
        return V(t, a);
    }
    static poissonDistribution(t) {
        return j(t);
    }
    static tTest(t, a) {
        return y(t, a);
    }
    static tTestTwoSample(t, a, s = 0) {
        return F(t, a, s);
    }
    static chunk(t, a) {
        return O(t, a);
    }
    static factorial(t) {
        return z(t);
    }
    static gamma(t) {
        return C(t);
    }
    static approxEqual(t, a, s) {
        return E(t, a, s);
    }
    static bisect(t, a, s, r, e) {
        return N(t, a, s, r, e);
    }
    static coefficientOfVariation(t) {
        return W(t);
    }
    static combinationsReplacement(t, a) {
        return B(t, a);
    }
    static combinations(t, a) {
        return G(t, a);
    }
    static combineMeans(t, a, s, r) {
        return H(t, a, s, r);
    }
    static combineVariances(t, a, s, r, e, i) {
        return I(t, a, s, r, e, i);
    }
    static cumulativeStdLogisticProbability(t) {
        return J(t);
    }
    static extent(t) {
        return K(t);
    }
    static gammaln(t) {
        return Q(t);
    }
    static jenks(t, a) {
        return U(t, a);
    }
    static logAverage(t) {
        return X(t);
    }
    static logit(t) {
        return Y(t);
    }
    static probit(t) {
        return Z(t);
    }
    static quantileRank(t, a) {
        return $(t, a);
    }
    static quickselect(t, a, s, r) {
        const e = [ ...t ];
        _(e, a, s, r);
        return e;
    }
    static subtractFromMean(t, a, s) {
        return tt(t, a, s);
    }
    static subtractFromAverage(t, a, s) {
        return tt(t, a, s);
    }
}

export { Statistics };