Class RegressionOutputV1

java.lang.Object
com.seeq.model.RegressionOutputV1

public class RegressionOutputV1 extends Object
Regression output from the formula result. Note that the `table` will also contain values.
  • Constructor Details

    • RegressionOutputV1

      public RegressionOutputV1()
  • Method Details

    • adjustedRSquared

      public RegressionOutputV1 adjustedRSquared(Double adjustedRSquared)
    • getAdjustedRSquared

      public Double getAdjustedRSquared()
      The measure of how close the data is to the regression line, adjusted for the number of input signals and samples
      Returns:
      adjustedRSquared
    • setAdjustedRSquared

      public void setAdjustedRSquared(Double adjustedRSquared)
    • errorSumSquares

      public RegressionOutputV1 errorSumSquares(Double errorSumSquares)
    • getErrorSumSquares

      public Double getErrorSumSquares()
      The standard error for the sum squares
      Returns:
      errorSumSquares
    • setErrorSumSquares

      public void setErrorSumSquares(Double errorSumSquares)
    • intercept

      public RegressionOutputV1 intercept(Double intercept)
    • getIntercept

      public Double getIntercept()
      The constant offset to add. 0 if forceThroughZero was true. This is the intercept for the output signal rather than the individual coefficients.
      Returns:
      intercept
    • setIntercept

      public void setIntercept(Double intercept)
    • interceptStandardError

      public RegressionOutputV1 interceptStandardError(Double interceptStandardError)
    • getInterceptStandardError

      public Double getInterceptStandardError()
      The standard error for the intercept
      Returns:
      interceptStandardError
    • setInterceptStandardError

      public void setInterceptStandardError(Double interceptStandardError)
    • isUncertain

      public RegressionOutputV1 isUncertain(Boolean isUncertain)
    • getIsUncertain

      public Boolean getIsUncertain()
      True if this regression is uncertain
      Returns:
      isUncertain
    • setIsUncertain

      public void setIsUncertain(Boolean isUncertain)
    • getRSquared

      public Double getRSquared()
      The measure of how close the data is to the regression line
      Returns:
      rSquared
    • regressionSumSquares

      public RegressionOutputV1 regressionSumSquares(Double regressionSumSquares)
    • getRegressionSumSquares

      public Double getRegressionSumSquares()
      The measure of how well the model matches the target
      Returns:
      regressionSumSquares
    • setRegressionSumSquares

      public void setRegressionSumSquares(Double regressionSumSquares)
    • suggestedPValueCutoff

      public RegressionOutputV1 suggestedPValueCutoff(Double suggestedPValueCutoff)
    • getSuggestedPValueCutoff

      public Double getSuggestedPValueCutoff()
      The value which the regression method suggests for ignoring coefficients
      Returns:
      suggestedPValueCutoff
    • setSuggestedPValueCutoff

      public void setSuggestedPValueCutoff(Double suggestedPValueCutoff)
    • equals

      public boolean equals(Object o)
      Overrides:
      equals in class Object
    • hashCode

      public int hashCode()
      Overrides:
      hashCode in class Object
    • toString

      public String toString()
      Overrides:
      toString in class Object