Value Members

1.  final def !=(arg0: Any): Boolean

   Definition Classes

   AnyRef → Any

2.  final def ##(): Int

   Definition Classes

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3.  final def ==(arg0: Any): Boolean

   Definition Classes

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4.  val add_1: Boolean

   Attributes

   protected

   Definition Classes

   GLM

5.  def apply(x_: MatrixD, t: VectorI, y: VectorD, levels: Int): ANCOVA

   Build an ANalysis of COVAriance (ANCOVA) model.

   Build an ANalysis of COVAriance (ANCOVA) model.

   x_

   the data/design matrix of continuous variables

   t

   the treatment/categorical variable vector

   y

   the response vector

   levels

   the number of treatment levels (1, ... levels)

   Definition Classes

   GLM

6.  def apply(x_: MatrixD, y: VectorD, cubic: Boolean): ResponseSurface

   Build a Response Surface model.

   Build a Response Surface model.

   x_

   the input vectors/points

   y

   the response vector

   cubic

   the order of the surface (false for quadratic, true for cubic)

   Definition Classes

   GLM

7.  def apply(ty: MatrixD, k: Int, w: Double): TrigRegression

   Build a Trigonometric Regression model.

   Build a Trigonometric Regression model.

   ty

   the combined input vector and response vector

   k

   the maximum multiplier in the trig function 'kwt'

   w

   the base displacement angle in radians

   Definition Classes

   GLM

8.  def apply(t: VectorD, y: VectorD, k: Int, w: Double): TrigRegression

   Build a Trigonometric Regression model.

   Build a Trigonometric Regression model. It makes a matrix using 'expand'.

   t

   the input vector: t_i expands to x_i

   y

   the response vector

   k

   the maximum multiplier in the trig function 'kwt'

   w

   the base displacement angle in radians

   Definition Classes

   GLM

9.  def apply(ty: MatrixD, k: Int): PolyRegression

   Build a Polynomial Regression model.

   Build a Polynomial Regression model.

   ty

   the combined input vector and response vector

   k

   the order of the polynomial

   Definition Classes

   GLM

10.  def apply(t: VectorD, y: VectorD, k: Int): PolyRegression

    Build a Polynomial Regression model.

    Build a Polynomial Regression model. It makes a matrix using 'expand'.

    t

    the input vector: t_i expands to x_i = [1, t_i, t_i^{2, ... t_i}k]

    y

    the response vector

    k

    the order of the polynomial

    Definition Classes

    GLM

11.  def apply(xy: MatrixD, transform: FunctionS2S): TranRegression

    Build a Transformed Multiple Linear Regression model.

    Build a Transformed Multiple Linear Regression model.

    xy

    the combined input/design m-by-n matrix and response m-vector

    transform

    the transformation function

    Definition Classes

    GLM

12.  def apply(x: MatrixD, y: VectorD, transform: FunctionS2S): TranRegression

    Build a Transformed Multiple Linear Regression model.

    Build a Transformed Multiple Linear Regression model.

    x

    the input/design m-by-n matrix

    y

    the response m-vector

    transform

    the transformation function (e.g., log)

    Definition Classes

    GLM

13.  def apply(xy: MatrixD, lambda: Double): RidgeRegression

    Build a Multiple Linear Robust Regression model.

    Build a Multiple Linear Robust Regression model.

    lambda

    the shrinkage parameter (0 => OLS) in the penalty term 'lambda * b dot b'

    Definition Classes

    GLM

14.  def apply(x: MatrixD, y: VectorD, lambda: Double): RidgeRegression

    Build a Multiple Linear Robust Regression model.

    Build a Multiple Linear Robust Regression model.

    x

    the centered input/design m-by-n matrix NOT augmented with a first column of ones

    y

    the centered response vector

    lambda

    the shrinkage parameter (0 => OLS) in the penalty term 'lambda * b dot b'

    Definition Classes

    GLM

15.  def apply(xy: MatrixD): Regression

    Build a Multiple Linear Regression model.

    Build a Multiple Linear Regression model.

    xy

    the combined input/design m-by-n matrix and response m-vector

    Definition Classes

    GLM

16.  def apply(x: MatrixD, y: VectorD): Regression

    Build a Multiple Linear Regression model.

    Build a Multiple Linear Regression model.

    x

    the input/design m-by-n matrix

    y

    the response m-vector

    Definition Classes

    GLM

17.  final def asInstanceOf[T0]: T0

    Definition Classes

    Any

18.  def clone(): AnyRef

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

19.  final def eq(arg0: AnyRef): Boolean

    Definition Classes

    AnyRef

20.  def equals(arg0: Any): Boolean

    Definition Classes

    AnyRef → Any

21.  def finalize(): Unit

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

    @throws( classOf[java.lang.Throwable] )

22.  final def getClass(): Class[_]

    Definition Classes

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23.  def hashCode(): Int

    Definition Classes

    AnyRef → Any

24.  final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

25.  final def ne(arg0: AnyRef): Boolean

    Definition Classes

    AnyRef

26.  final def notify(): Unit

    Definition Classes

    AnyRef

27.  final def notifyAll(): Unit

    Definition Classes

    AnyRef

28.  def setAdd_1(_add_1: Boolean = true): Unit

    Explicitly set the add_1 flag (column of all ones corresponding to b_0).

    Explicitly set the add_1 flag (column of all ones corresponding to b_0).

    _add_1

    the value to set the add_1 flag to

    Definition Classes

    GLM

29.  def setTechnique(_technique: RegTechnique = QR): Unit

    Explicitly set the regression technique to use.

    Explicitly set the regression technique to use.

    _technique

    the value to set technique to

    Definition Classes

    GLM

30.  final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes

    AnyRef

31.  val technique: RegTechnique.Value

    Attributes

    protected

    Definition Classes

    GLM

32.  def toString(): String

    Definition Classes

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33.  final def wait(): Unit

    Definition Classes

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    Annotations

    @throws( ... )

34.  final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

35.  final def wait(arg0: Long): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )