case class TrendLine extends Product with Serializable
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final
def
!=(arg0: Any): Boolean
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##(): Int
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==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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- def calculateResidual(point: Point): Double
- def calculateResiduals(points: List[Point]): List[Double]
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def
calculateSigmaResiduals(extraResiduals: List[YAxisType]): Double
calculates sigma residuals using this.residuals plus extraResiduals
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def
clone(): AnyRef
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- @throws( ... ) @native() @HotSpotIntrinsicCandidate()
- def containsPoint(xPosition: XAxisType): Boolean
- def containsPoint(point: Point): Boolean
- val end: XAxisType
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final
def
eq(arg0: AnyRef): Boolean
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- def estimate(x: XAxisType): YAxisType
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final
def
getClass(): Class[_]
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- @native() @HotSpotIntrinsicCandidate()
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def
getPointsContained(sortedPoints: List[Point]): List[Point]
retrieves a subset of sortedPoints that are contained in this trend line, i.e.
retrieves a subset of sortedPoints that are contained in this trend line, i.e. returned points are positioned between start and end
- sortedPoints
a list of points sorted by x-value ascending
- def getResiduals: List[Double]
- val intercept: Double
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def
intersectAhead(x: Double, secondTrendLine: TrendLine): Boolean
true if x >= intersect between this and secondTrendLine
true if x >= intersect between this and secondTrendLine
is equivalent to secondTrendLine.intersectAhead(x, this)
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def
intersectAt(secondTrendLine: TrendLine): Option[Double]
calculates the x-position were two trend lines intercept, None if lines are parallel
calculates the x-position were two trend lines intercept, None if lines are parallel
is equivalent to secondTrendLine.intersectAt(this)
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final
def
isInstanceOf[T0]: Boolean
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def
lengthOfTrend: XAxisType
end - start
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def
likelihoodOfCluster(points: List[Point], sigmaResiduals: Double): Double
calculates likelihood of multiple points
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def
likelihoodOfPoint(point: Point, sigmaResiduals: Double): Double
calculates likelihood of a single point, always use this when making the calculation on multiple points, so it doesn't have to recalculate the same value for sigmaResiduals multiple times
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final
def
ne(arg0: AnyRef): Boolean
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def
notify(): Unit
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final
def
notifyAll(): Unit
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- val residuals: List[Double]
- val size: Int
- val slope: Double
- val start: XAxisType
- def statistics: NumericSeriesStatistics
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def
synchronized[T0](arg0: ⇒ T0): T0
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wait(arg0: Long, arg1: Int): Unit
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wait(arg0: Long): Unit
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final
def
wait(): Unit
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- val xMean: Double
- val xSquaredMeanDiff: Double
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finalize(): Unit
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