class StatCounter extends Serializable
A class for tracking the statistics of a set of numbers (count, mean and variance) in a numerically robust way. Includes support for merging two StatCounters. Based on Welford and Chan's algorithms for running variance.
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- StatCounter.scala
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Instance Constructors
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new
StatCounter()
Initialize the StatCounter with no values.
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new
StatCounter(values: TraversableOnce[Double])
Initialize the StatCounter with the given values.
Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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- protected[lang]
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- @throws( ... ) @native()
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def
copy(): StatCounter
Clone this StatCounter
- def count: Long
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
finalize(): Unit
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final
def
getClass(): Class[_]
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def
hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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- def max: Double
- def mean: Double
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def
merge(other: StatCounter): StatCounter
Merge another StatCounter into this one, adding up the internal statistics.
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def
merge(values: TraversableOnce[Double]): StatCounter
Add multiple values into this StatCounter, updating the internal statistics.
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def
merge(value: Double): StatCounter
Add a value into this StatCounter, updating the internal statistics.
- def min: Double
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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def
popStdev: Double
Return the population standard deviation of the values.
Return the population standard deviation of the values.
- Annotations
- @Since( "2.1.0" )
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def
popVariance: Double
Return the population variance of the values.
Return the population variance of the values.
- Annotations
- @Since( "2.1.0" )
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def
sampleStdev: Double
Return the sample standard deviation of the values, which corrects for bias in estimating the variance by dividing by N-1 instead of N.
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def
sampleVariance: Double
Return the sample variance, which corrects for bias in estimating the variance by dividing by N-1 instead of N.
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def
stdev: Double
Return the population standard deviation of the values.
- def sum: Double
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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def
variance: Double
Return the population variance of the values.
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
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