lerfob.predictor.mathilde.recruitment

Class MathildeRecruitmentNumberPredictor

java.lang.Object

repicea.simulation.SensitivityAnalysisParameter<ModelParameterEstimates>

repicea.simulation.REpiceaPredictor

lerfob.predictor.mathilde.recruitment.MathildeRecruitmentNumberPredictor

All Implemented Interfaces:

java.io.Serializable

public class MathildeRecruitmentNumberPredictor
extends REpiceaPredictor

This class predicts the number of recruits for each species of the MATHILDE model.

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class repicea.simulation.REpiceaPredictor

REpiceaPredictor.CruiseLine, REpiceaPredictor.ErrorTermGroup, REpiceaPredictor.IntervalNestedInPlotDefinition

Field Summary

Fields

Modifier and Type	Field and Description
static double	REFERENCE_AREA_HA

Fields inherited from class repicea.simulation.REpiceaPredictor

DefaultZeroIndex, isRandomEffectsVariabilityEnabled, isResidualVariabilityEnabled, listeners, oXVector

Fields inherited from class repicea.simulation.SensitivityAnalysisParameter

isParametersVariabilityEnabled

Constructor Summary

Constructors

Modifier	Constructor and Description
	MathildeRecruitmentNumberPredictor(boolean isVariabilityEnabled) Constructor
protected	MathildeRecruitmentNumberPredictor(boolean isParameterVariabilityEnabled, boolean isResidualVariabilityEnabled)

Method Summary

Modifier and Type	Method and Description
protected double	getFalseZeroProbability(Matrix betaZero, MathildeRecruitmentStand stand, MathildeTreeSpeciesProvider.MathildeTreeSpecies species)
protected Matrix	getMarginalPredictionsForThisStandAndSpecies(MathildeRecruitmentStand stand, MathildeTreeSpeciesProvider.MathildeTreeSpecies species, int resolution, boolean isResidualVariabilityEnabled) This method returns the marginal prediction for a single species.
protected double	getNegativeBinomialMean(Matrix betaCount, MathildeRecruitmentStand stand, MathildeTreeSpeciesProvider.MathildeTreeSpecies species)
protected void	init() This method reads all the parameters in .csv files and stores the estimates into members defaultBeta, defaultResidualError, and defaultRandomEffects.
Matrix	predictNumberOfRecruits(MathildeRecruitmentStand stand) This method returns the number of recruits for each species.

Methods inherited from class repicea.simulation.REpiceaPredictor

addModelBasedSimulatorListener, doBlupsExistForThisSubject, doesThisSubjectHaveResidualErrorTerm, doRandomDeviatesExistForThisSubject, fireModelBasedSimulatorEvent, fireRandomEffectDeviateGeneratedEvent, getBlupsForThisSubject, getCruiseLineForThisSubject, getDefaultRandomEffects, getDefaultRandomEffects, getDefaultResidualError, getGaussianErrorTerms, getIntervalNestedInPlotDefinition, getParametersForThisRealization, getRandomEffectsForThisSubject, getResidualError, getResidualErrorForThisSubject, getSubjectPlusMonteCarloSpecificId, getSubjectPlusMonteCarloSpecificId, hasSubjectBeenTestedForBlups, recordSubjectTestedForBlups, removeModelBasedSimulatorListener, setBlupsForThisSubject, setDefaultRandomEffects, setDefaultResidualError, setDeviatesForRandomEffectsOfThisSubject, setParameterEstimates, simulateDeviatesForRandomEffectsOfThisSubject

Methods inherited from class repicea.simulation.SensitivityAnalysisParameter

getParameterEstimates

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

REFERENCE_AREA_HA

public static final double REFERENCE_AREA_HA

See Also:

Constant Field Values

Constructor Detail

MathildeRecruitmentNumberPredictor

public MathildeRecruitmentNumberPredictor(boolean isVariabilityEnabled)

Constructor

Parameters:

isVariabilityEnabled - true to enable the stochastic variability.

MathildeRecruitmentNumberPredictor

protected MathildeRecruitmentNumberPredictor(boolean isParameterVariabilityEnabled,
                                             boolean isResidualVariabilityEnabled)

Method Detail

init

protected void init()

Description copied from class: REpiceaPredictor

This method reads all the parameters in .csv files and stores the estimates into members defaultBeta, defaultResidualError, and defaultRandomEffects.

Specified by:

init in class REpiceaPredictor

predictNumberOfRecruits

public Matrix predictNumberOfRecruits(MathildeRecruitmentStand stand)

This method returns the number of recruits for each species.

Parameters:

stand - a MathildeRecruitmentStand instance

Returns:

a Matrix

getMarginalPredictionsForThisStandAndSpecies

protected Matrix getMarginalPredictionsForThisStandAndSpecies(MathildeRecruitmentStand stand,
                                                              MathildeTreeSpeciesProvider.MathildeTreeSpecies species,
                                                              int resolution,
                                                              boolean isResidualVariabilityEnabled)

This method returns the marginal prediction for a single species. If the isResidualVariabilityEnabled option is set to false then the resolution parameter is useless.

Parameters:

stand - a MathildeRecruitmentStand instance

species - a MathildeTreeSpecies instance

resolution - the maximum number of recruits

isResidualVariabilityEnabled - true to enabled the stochastic variability.

Returns:

a row vector (the column index is the number of recruits

getNegativeBinomialMean

protected double getNegativeBinomialMean(Matrix betaCount,
                                         MathildeRecruitmentStand stand,
                                         MathildeTreeSpeciesProvider.MathildeTreeSpecies species)

getFalseZeroProbability

protected double getFalseZeroProbability(Matrix betaZero,
                                         MathildeRecruitmentStand stand,
                                         MathildeTreeSpeciesProvider.MathildeTreeSpecies species)