KSLCore/ksl.utilities.distributions/Distribution

Distribution

Constructors

constructor(name: String? = null)

Types

object Companion

Properties

open override val id: Int

open override var label: String?

open override val name: String

open val randomVariable: RVariableIfc

Functions

abstract fun cdf(x: Double): Double

Returns the F(x) = Pr{X <= x} where F represents the cumulative distribution function

open fun cdf(x: DoubleArray): DoubleArray

Returns an array of probabilities each representing F(x_i). The CDF is evaluated for each point in the input array x and the probabilities are returned in the returned array.

open fun cdf(interval: Interval): Double

Returns the probability of being in the interval, F(upper limit) - F(lower limit) Be careful, this is Pr{lower limit < = X < = upper limit} which includes the lower limit and has implications if the distribution is discrete

open fun cdf(x1: Double, x2: Double): Double

Returns the Pr{x1 <= X <= x2} for the distribution. Be careful, this is Pr{x1 <= X <= x2} which includes the lower limit and has implications if the distribution is discrete

complementaryCDF

open fun complementaryCDF(x: Double): Double

Computes the complementary cumulative probability distribution function for given value of x. This is P{X > x}

abstract fun instance(): DistributionIfc

abstract fun invCDF(p: Double): Double

Provides the inverse cumulative distribution function for the distribution

open fun invCDF(probabilities: DoubleArray): DoubleArray

Computes x_p where P(X <= x_p) = p for the supplied array of probabilities. Requires that the values within the supplied array are in (0,1)

abstract fun mean(): Double

Returns the mean or expected value of a distribution

abstract fun parameters(): DoubleArray

Gets the parameters

abstract fun parameters(params: DoubleArray)

Sets the parameters

open fun randomVariable(streamNum: Int): RVariableIfc

abstract fun randomVariable(stream: RNStreamIfc): RVariableIfc

standardDeviation

open fun standardDeviation(): Double

Returns the standard deviation for the distribution as the square root of the variance if it exists

abstract fun variance(): Double

Returns the variance of the distribution if defined