Properties

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abstract val binArray: Array<HistogramBin>

Returns an array of Bins based on the current state of the histogram

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abstract val binCounts: DoubleArray
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abstract val bins: List<HistogramBin>

Returns a List of Bins based on the current state of the histogram

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abstract val breakPoints: DoubleArray
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A simple estimate of the "density" function for each bin using bin fraction/bin width values for each bin The bin width must be constant across the bins and not equal to 0.0

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The first bin's lower limit

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The last bin's upper limit

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abstract val numberBins: Int
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abstract val overFlowCount: Double

The number of observations that fell past the last bin's upper limit

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abstract val totalCount: Double

Total number of observations collected including overflow and underflow

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abstract val underFlowCount: Double

The number of observations that fell below the first bin's lower limit

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Functions

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open fun asString(): String
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abstract fun bin(x: Double): HistogramBin

The bin that x falls in. The bin is a copy. It will not reflect observations collected after this call.

abstract fun bin(binNum: Int): HistogramBin

Returns an instance of a Bin for the supplied bin number The bin does not reflect changes to the histogram after this call. May throw IndexOutOfBoundsException

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abstract fun binCount(x: Double): Double

Returns the current bin count for the bin associated with x

abstract fun binCount(binNum: Int): Double

Returns the bin count for the indicated bin

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abstract fun binFraction(x: Double): Double

Returns the fraction of the data relative to those tabulated in the bins for the bin number associated with the x

abstract fun binFraction(binNum: Int): Double

Returns the fraction of the data relative to those tabulated in the bins for the supplied bin number

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abstract fun binNumber(x: Double): Int

Bins are numbered starting at 1 through the number of bins

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Returns the probability for each bin of the histogram based on a continuous interval interpretation of the bin. The distribution, cdf must implement the ContinuousDistributionIfc interface

Returns the probability for each bin of the histogram based on an open integer range interpretation of the bin. The discrete distribution, discreteCDF must implement the ProbInRangeIfc interface

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The breakpoints must be finite.

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open fun createPWCEmpiricalRV(streamNum: Int = 0, streamProvider: RNStreamProviderIfc = KSLRandom.DefaultRNStreamProvider, name: String? = null): PWCEmpiricalRV

The breakpoints must be finite.

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abstract fun cumulativeBinCount(x: Double): Double

Returns the cumulative count of all bins up to and including the bin containing the value x

abstract fun cumulativeBinCount(binNum: Int): Double

Returns the cumulative count of all the bins up to and including the indicated bin number

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Returns the cumulative fraction of the data up to and including the bin containing the value of x

abstract fun cumulativeBinFraction(binNum: Int): Double

Returns the cumulative fraction of the data up to and including the indicated bin number

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abstract fun cumulativeCount(x: Double): Double

Returns the cumulative count of all the data (including underflow and overflow) for all bins up to and including the bin containing x

abstract fun cumulativeCount(binNum: Int): Double

Returns the cumulative count of all the data (including underflow and overflow) up to and including the indicated bin

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abstract fun cumulativeFraction(x: Double): Double

Returns the cumulative fraction of all the data up to an including the bin containing the value x, (includes over and under flow)

abstract fun cumulativeFraction(binNum: Int): Double

Returns the cumulative fraction of all the data up to and including the supplied bin (includes over and under flow)

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Returns the expected count for each bin of the histogram based on a continuous interval interpretation of the bin. The distribution, cdf must implement the ContinuousDistributionIfc interface

open fun expectedCounts(discreteCDF: ProbInRangeIfc): DoubleArray

Returns the expected count for each bin of the histogram based on a continuous interval interpretation of the bin. The discrete distribution, discreteCDF must implement the ProbInRangeIfc interface

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abstract fun findBin(x: Double): HistogramBin
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The data of the histogram bins

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open fun histogramPlot(proportions: Boolean = true): HistogramPlot

Creates a plot for the histogram. The parameter, proportions indicates whether proportions (true) or frequencies (false) will be shown on the plot. The default is true.

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Converts the histogram bin data into a dataframe representation