KSLCore/ksl.utilities.distributions.fitting.estimators/TriangularParameterEstimator

TriangularParameterEstimator

object TriangularParameterEstimator : ParameterEstimatorIfc, MVBSEstimatorIfc, IdentityIfc

The approach is based on estimating the min and max via the recommended approach for the uniform distribution. Then, the mode is estimated by solving for it in terms of the sample average.

Properties

checkRange

open override val checkRange: Boolean = false

Indicates if the estimator requires that the range of the data be checked for a shift before the estimation process.

open override val id: Int

label

open override var label: String?

name

open override val name: String

names

open override val names: List<String>

The name to associate with each dimension of the array that is returned by estimate(). The names should be unique. The order of the list of names should match the order of elements in the returned array.

rvType

open override val rvType: RVParametersTypeIfc

The type of random variable for which this estimator estimates parameters.

Functions

estimate

open override fun estimate(data: DoubleArray): DoubleArray

If the estimation process is not successful, then an empty array is returned.

estimateParameters

open override fun estimateParameters(data: DoubleArray, statistics: StatisticIfc): EstimationResult

Estimates the parameters associated with some distribution. The returned EstimationResult needs to be consistent with the intent of the desired distribution. Note the meaning of the fields associated with EstimationResult