KSLCore/ksl.utilities.statistic/BootstrapEstimate

BootstrapEstimate

open class BootstrapEstimate(val name: String, val originalDataSampleSize: Int, val originalDataEstimate: Double, val bootstrapEstimates: DoubleArray) : BootstrapEstimateIfc

Constructors

BootstrapEstimate

constructor(name: String, originalDataSampleSize: Int, originalDataEstimate: Double, bootstrapEstimates: DoubleArray)

Properties

acrossBootstrapAverage

open val acrossBootstrapAverage: Double

acrossBootstrapStatistics

open override val acrossBootstrapStatistics: StatisticIfc

bootstrapBiasEstimate

open val bootstrapBiasEstimate: Double

This is acrossBootstrapAverage - originalDataEstimate

bootstrapDifferences

open val bootstrapDifferences: DoubleArray

Each element is the bootstrap estimate for sample i minus originalDataEstimate

bootstrapEstimates

override val bootstrapEstimates: DoubleArray

bootstrapStdErrEstimate

open val bootstrapStdErrEstimate: Double

This is the standard deviation of the across bootstrap observations of the estimator for each bootstrap generated

defaultCILevel

open override var defaultCILevel: Double

the default confidence interval level

label

open override var label: String?

name

override val name: String

A name for the estimate

numberOfBootstraps

open val numberOfBootstraps: Int

The number of bootstrap samples that were used to produce the bootstrap estimate

originalDataEstimate

override val originalDataEstimate: Double

originalDataSampleSize

override val originalDataSampleSize: Int

The sample size of the original data set

standardizedBootstrapDifferences

open val standardizedBootstrapDifferences: DoubleArray

Each element is the bootstrap estimate for sample i minus getOriginalDataEstimate() divided by getBootstrapStdErrEstimate()

Functions

asString

open fun asString(): String

basicBootstrapCI

open fun basicBootstrapCI(level: Double = defaultCILevel): Interval

The "basic" method, but with no bias correction. This is the so-called centered percentile method (2θ − Bu , 2θ − Bl ) where θ is the bootstrap estimator and Bu is the 1 - alpha/2 percentile and Bl is the lower (alpha/2) percentile, where level = 1-alpha of the bootstrap replicates.

percentileBootstrapCI

open fun percentileBootstrapCI(level: Double = defaultCILevel): Interval

The "percentile" method, but with no bias correction. This is the percentile method (Bl , Bu ) where Bu is the 1 - alpha/2 percentile and Bl is the lower (alpha/2) percentile, where level = 1-alpha of the bootstrap replicates

stdNormalBootstrapCI

open fun stdNormalBootstrapCI(level: Double = defaultCILevel): Interval

Gets the standard normal based bootstrap confidence interval. Not recommended.

toString

open override fun toString(): String