Statistic

scalation.mathstat.Statistic
See theStatistic companion class
object Statistic

The Statistic companion object provides additional values and functions.

Attributes

Companion
class
Graph
Supertypes
class Object
trait Matchable
class Any
Self type
Statistic.type

Members list

Value members

Concrete methods

def aggregate(subStats: ArrayBuffer[Statistic], name: String, unbiased: Boolean): Statistic

Aggregate the sub-statistics by summing all accumulators and determining new overall extreme values.

Aggregate the sub-statistics by summing all accumulators and determining new overall extreme values.

Value parameters

name

the name for the aggregated statistic

subStats

the list of sub-statistics

unbiased

whether the estimators are restricted to be unbiased

Attributes

def apply(n: Int, sum: Double, sumAb: Double, sumSq: Double, minX: Double, maxX: Double, name: String, unbiased: Boolean): Statistic

Create a statistical object and set its accumulators and extreme values.

Create a statistical object and set its accumulators and extreme values.

Value parameters

maxX

the maximum sample value

minX

the minimum sample value

n

the number of samples

name

the name for this statistic (e.g., 'waitingTime')

sum

sum of the sample values

sumAb

sum of the sample absolute values

sumSq

sum of the sample values squared

unbiased

whether the estimators are restricted to be unbiased

Attributes

def tallyAll(x: VectorD): Double

Tally all the values and return the sum.

Tally all the values and return the sum.

Value parameters

x

the vector of values to tally (e.g., time in sytem)

Attributes

Concrete fields

val label: Array[String]

The statistical labels (column headers) as an Array

The statistical labels (column headers) as an Array

Attributes

val labels: String

The statistical labels (column headers) as a formatted String

The statistical labels (column headers) as a formatted String

Attributes

val line: String

The line separator

The line separator

Attributes