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

BinomialMaxParameterEstimator

object BinomialMaxParameterEstimator : ParameterEstimatorIfc, MVBSEstimatorIfc, IdentityIfc

Estimates the probability of success (p) and number of trials (n) for the binomial distribution based. The number of trials is estimated based on the maximum observed value adjusted based on range estimation for uniform(min, max) distribution.

The data must not contain negative values. The estimation process assumes that the supplied data are integer valued counts over the range {0,1,2,..., n}. That is this parameterization represents the number of success in n trials. The estimation process does not ensure that n is integer valued.

Properties

checkRange

open override val checkRange: Boolean = true

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