scalation.analytics

SimpleRegression

class SimpleRegression extends Predictor with Error

The SimpleRegression class supports simple linear regression. In this case, the vector 'x' consists of the constant one and a single variable 'x_1', i.e., (1, x1). Fit the parameter vector 'b' in the regression equation

y = b dot x + e = (b0, b1) dot (1, x1) + e = b0 + b1 * x1 + e

where 'e' represents the residuals (the part not explained by the model).

Linear Supertypes
Error, Predictor, AnyRef, Any
Ordering
  1. Alphabetic
  2. By inheritance
Inherited
  1. SimpleRegression
  2. Error
  3. Predictor
  4. AnyRef
  5. Any
  1. Hide All
  2. Show all
Learn more about member selection
Visibility
  1. Public
  2. All

Instance Constructors

  1. new SimpleRegression(x: MatrixD, y: VectorD)

    x

    the input/design matrix augmented with a first column of ones

    y

    the response vector

Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any

  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  7. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  8. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  9. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  10. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  11. def fit: (VectorD, Double)

    Return the fit (parameter vector b, quality of fit rSquared)

  12. def flaw(method: String, message: String): Unit

    Show the flaw by printing the error message.

    Show the flaw by printing the error message.

    method

    the method where the error occurred

    message

    the error message

    Definition Classes
    Error

  13. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any

  14. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  15. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  16. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  17. final def notify(): Unit

    Definition Classes
    AnyRef

  18. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  19. def predict(z: MatrixD): VectorD

    Predict the value of y = f(z) by evaluating the formula y = b dot z for each row of matrix z.

    Predict the value of y = f(z) by evaluating the formula y = b dot z for each row of matrix z.

    z

    the new matrix to predict

    Definition Classes
    SimpleRegression → Predictor

  20. def predict(z: VectorD): Double

    Predict the value of y = f(z) by evaluating the formula y = b dot z, i.

    Predict the value of y = f(z) by evaluating the formula y = b dot z, i.e.0, (b0, b1) dot (1.0, z1).

    z

    the new vector to predict

    Definition Classes
    SimpleRegression → Predictor

  21. def predict(z: VectorI): Double

    Given a new discrete data vector z, predict the y-value of f(z).

    Given a new discrete data vector z, predict the y-value of f(z).

    z

    the vector to use for prediction

    Definition Classes
    Predictor

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

    Definition Classes
    AnyRef

  23. def toString(): String

    Definition Classes
    AnyRef → Any

  24. def train(): Unit

    Train the predictor by fitting the parameter vector (b-vector) in the simple regression equation y = b dot x + e = (b0, b1) dot (1.

    Train the predictor by fitting the parameter vector (b-vector) in the simple regression equation y = b dot x + e = (b0, b1) dot (1.0, x1) + e using the least squares method.

    Definition Classes
    SimpleRegression → Predictor
    See also

    http://www.analyzemath.com/statistics/linear_regression.html

  25. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  27. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Error

Inherited from Predictor

Inherited from AnyRef

Inherited from Any

Ungrouped