Class PolynomialRegression

constructor

• new PolynomialRegression(
      x: NumberArray,
      y: NumberArray,
      degree: number | NumberArray,
      options?: PolynomialRegressionOptions,
  ): PolynomialRegression

• Parameters

  • x: NumberArray

    independent or explanatory variable
  • y: NumberArray

    dependent or response variable
  • degree: number | NumberArray

    degree of the polynomial regression, or array of powers to be used. When degree is an array, intercept at zero is forced to false/ignored.
  • options: PolynomialRegressionOptions = {}

    • interceptAtZero

      force the polynomial regression so that f(0) = 0

  Returns PolynomialRegression

  Example

  `new PolynomialRegression(x, y, 2)`, in this case, you can pass the option `interceptAtZero`, if you need it.
  Copy

  Example

  `new PolynomialRegression(x, y, [1, 3, 5])`
  Each of the degrees corresponds to a column, so if you have them switched, just do:
  Copy

  Example

  `new PolynomialRegression(x, y, [3, 1, 5])`
  Copy

coefficients

degree

powers

_predict

• _predict(x: number): number

• Parameters

  • x: number

  Returns number

_toFormula

• _toFormula(precision: number, isLaTeX: boolean): string

• Parameters

  • precision: number
  • isLaTeX: boolean

  Returns string

toJSON

• toJSON(): {
      coefficients: number[];
      degree: number;
      name: string;
      powers: number[];
  }

• Returns { coefficients: number[]; degree: number; name: string; powers: number[] }

toLaTeX

• toLaTeX(precision: number): string

• Parameters

  • precision: number

  Returns string

toString

• toString(precision: number): string

• Parameters

  • precision: number

  Returns string

Staticload

• load(
      json: {
          coefficients: number[];
          degree: number;
          name: string;
          powers: number[];
      },
  ): PolynomialRegression

• Parameters

  • json: { coefficients: number[]; degree: number; name: string; powers: number[] }

  Returns PolynomialRegression