Packages

class Fit extends AnyRef

The Fit class provides methods to determine basic quality of fit measures.

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Known Subclasses
ExpRegression, LassoRegression, NonLinRegression, NullModel, Perceptron, PoissonRegression, PredictorMat, Regression, Regression_WLS, ResponseSurface, RidgeRegression, SimpleRegression, SimplerRegression, TranRegression, Regression, RidgeRegression
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Instance Constructors

  1. new Fit(y: VectoD, n: Int, df: (Double, Double) = (0.0, 0.0))

    y

    the values in the m-dimensional response vector

    n

    the number of parameters (b.dim)

    df

    the degrees of freedom (df._1, df._2) for (regression, error)

Value Members

  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  3. final def ==(arg0: Any): Boolean
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  4. final def asInstanceOf[T0]: T0
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  5. def clone(): AnyRef
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  6. val df: (Double, Double)
  7. def diagnose(e: VectoD, w: VectoD = null, yp: VectoD = null): Unit

    Given the error/residual vector, compute the quality of fit measures.

    Given the error/residual vector, compute the quality of fit measures.

    e

    the corresponding m-dimensional error vector (y - yp)

    w

    the weights on the instances

    yp

    the predicted response vector (x * b)

  8. final def eq(arg0: AnyRef): Boolean
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  9. def equals(arg0: Any): Boolean
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  10. def f_(z: Double): String

    Format a double value.

    Format a double value.

    z

    the double value to format

  11. def finalize(): Unit
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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  12. def fit: VectoD

    Return the quality of fit including 'sst', 'sse', 'mse0', rmse', 'mae', 'rSq', 'df._2', 'rBarSq', 'fStat', 'aic', 'bic'.

    Return the quality of fit including 'sst', 'sse', 'mse0', rmse', 'mae', 'rSq', 'df._2', 'rBarSq', 'fStat', 'aic', 'bic'. Note, if 'sse > sst', the model introduces errors and the 'rSq' may be negative, otherwise, R^2 ('rSq') ranges from 0 (weak) to 1 (strong). Note that 'rSq' is the number 5 measure. Override to add more quality of fit measures.

  13. def fitLabel: Seq[String]

    Return the labels for the quality of fit measures.

    Return the labels for the quality of fit measures. Override to add more quality of fit measures.

  14. def fitMap: Map[String, String]

    Build a map of quality of fit measures (use of LinedHashMap makes it ordered).

    Build a map of quality of fit measures (use of LinedHashMap makes it ordered). Override to add more quality of fit measures.

  15. final def getClass(): Class[_]
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  16. def hashCode(): Int
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  17. val index_rSq: Int
  18. final def isInstanceOf[T0]: Boolean
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  19. def mse_: Double

    Return the mean of squares for error (sse / df._2).

    Return the mean of squares for error (sse / df._2). Must call diagnose first.

  20. final def ne(arg0: AnyRef): Boolean
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  21. final def notify(): Unit
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  22. final def notifyAll(): Unit
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  23. def sumCoeff(b: VectoD, stdErr: VectoD = null): String

    Produce the summary report portion for the cofficients.

    Produce the summary report portion for the cofficients.

    b

    the parameters/coefficients for the model

  24. def summary(b: VectoD, stdErr: VectoD = null): String

    Produce a summary report with diagnostics for each predictor 'x_j' and the overall quality of fit.

    Produce a summary report with diagnostics for each predictor 'x_j' and the overall quality of fit.

    b

    the parameters/coefficients for the model

  25. final def synchronized[T0](arg0: ⇒ T0): T0
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  26. def toString(): String
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  27. final def wait(): Unit
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  28. final def wait(arg0: Long, arg1: Int): Unit
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  29. final def wait(arg0: Long): Unit
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