Packages

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, x_1). Fit the parameter vector 'b' in the regression equation

y = b dot x + e = (b_0, b_1) dot (1, x_1) + e = b_0 + b_1 * x_1 + e

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

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Error, Predictor, AnyRef, Any
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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. def coefficient: VectoD

    Return the vector of coefficient/parameter values.

    Return the vector of coefficient/parameter values.

    Definition Classes
    Predictor
  2. def diagnose(yy: VectoD): Unit

    Compute diagostics for the regression model.

    Compute diagostics for the regression model.

    yy

    the response vector

    Definition Classes
    SimpleRegression → Predictor
  3. def fit: VectorD

    Return the quality of fit including.

    Return the quality of fit including.

    Definition Classes
    SimpleRegression → Predictor
  4. def fitLabels: Seq[String]

    Return the labels for the fit.

    Return the labels for the fit.

    Definition Classes
    SimpleRegression → Predictor
  5. final def flaw(method: String, message: String): Unit
    Definition Classes
    Error
  6. def predict(z: VectoD): Double

    Predict the value of y = f(z) by evaluating the formula y = b dot z, i.e.0, (b_0, b_1) dot (1, z_1).

    Predict the value of y = f(z) by evaluating the formula y = b dot z, i.e.0, (b_0, b_1) dot (1, z_1).

    z

    the new vector to predict

    Definition Classes
    SimpleRegression → Predictor
  7. def predict(z: VectoI): 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
  8. def residual: VectoD

    Return the vector of residuals/errors.

    Return the vector of residuals/errors.

    Definition Classes
    Predictor
  9. def train(): Unit

    Train the predictor by fitting the parameter vector (b-vector) in the simple regression equation for the response passed into the class 'y'.

    Train the predictor by fitting the parameter vector (b-vector) in the simple regression equation for the response passed into the class 'y'.

    Definition Classes
    SimpleRegression → Predictor
  10. def train(yy: VectoD): Unit

    Train the predictor by fitting the parameter vector (b-vector) in the simple regression equation

    Train the predictor by fitting the parameter vector (b-vector) in the simple regression equation

    y = b dot x + e = (b_0, b_1) dot (1, x_1) + e

    using the least squares method.

    yy

    the response vector

    Definition Classes
    SimpleRegression → Predictor
    See also

    www.analyzemath.com/statistics/linear_regression.html