Package com.irurueta.numerical

Class HistogramMaximumLikelihoodEstimator

java.lang.Object

com.irurueta.numerical.MaximumLikelihoodEstimator

com.irurueta.numerical.HistogramMaximumLikelihoodEstimator

public class HistogramMaximumLikelihoodEstimator
extends MaximumLikelihoodEstimator

Class to estimate the most likely value from a series of samples assumed to be normally distributed. This implementation will compute a histogram of the probability distribution function of all the provided samples. The probability distribution function is computed by aggregating all the samples as a series of Gaussian functions with a small sigma and centered at the exact value of the sample.

Field Summary

Fields

Modifier and Type	Field	Description
private double[]	bins	Number of samples contained on each bin.
static final int	DEFAULT_NUMBER_OF_BINS	Default number of bins to be used on the histogram.
static final double	EPS	Value to be considered as the machine precision.
private double[]	gaussian	Array containing the Gaussian values corresponding to each bin for a single sample.
static final int	MIN_NUMBER_OF_BINS	Minimum number of bins allowed on the histogram.
private int	numberOfBins	Number of bins to be used on the histogram.

Fields inherited from class com.irurueta.numerical.MaximumLikelihoodEstimator

areMinMaxAvailable, DEFAULT_GAUSSIAN_SIGMA, DEFAULT_METHOD, gaussianSigma, inputData, locked, maxValue, MIN_GAUSSIAN_SIGMA, minValue

Constructor Summary

Constructors

Constructor	Description
HistogramMaximumLikelihoodEstimator()	Empty constructor.
HistogramMaximumLikelihoodEstimator(double[] inputData, double gaussianSigma, int numberOfBins)	Constructor.
HistogramMaximumLikelihoodEstimator(double minValue, double maxValue, double[] inputData, double gaussianSigma, int numberOfBins)	Constructor.
HistogramMaximumLikelihoodEstimator(double gaussianSigma, int numberOfBins)	Constructor.

Method Summary

Modifier and Type	Method	Description
protected void	computeGaussian(double[] gaussian, double centerPos)	Internal method to compute values of Gaussian vector assumed to be centered at provided value.
double	estimate()	Starts the estimation of the most likely value contained within provided input data array.
MaximumLikelihoodEstimatorMethod	getMethod()	Returns method to be used for maximum likelihood estimation, which for this class is MaximumLikelihoodEstimatorMethod.
int	getNumberOfBins()	Returns number of bins to be used on the histogram.
private void	internalSetNumberOfBins(int numberOfBins)	Internal method to set number of bins to be used on the histogram.
void	setNumberOfBins(int numberOfBins)	Sets number of bins to be used on the histogram.

Methods inherited from class com.irurueta.numerical.MaximumLikelihoodEstimator

areMinMaxValuesAvailable, computeMinMaxValues, create, create, create, create, create, create, create, create, create, getGaussianSigma, getInputData, getMaxValue, getMinValue, isInputDataAvailable, isLocked, isReady, setGaussianSigma, setInputData, setInputData, setMinMaxValues

Methods inherited from class java.lang.Object

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

Field Details

DEFAULT_NUMBER_OF_BINS

public static final int DEFAULT_NUMBER_OF_BINS

Default number of bins to be used on the histogram.

See Also:

• Constant Field Values

MIN_NUMBER_OF_BINS

public static final int MIN_NUMBER_OF_BINS

Minimum number of bins allowed on the histogram.

See Also:

• Constant Field Values

EPS

public static final double EPS

Value to be considered as the machine precision.

See Also:

• Constant Field Values

numberOfBins

private int numberOfBins

Number of bins to be used on the histogram. The larger the value the more precise results will be but more data will be needed to obtain statistically meaningful data so that enough samples are present on each bin.

bins

private double[] bins

Number of samples contained on each bin. The number of samples is not an integer because the Gaussians of each sample will only have a value equal to one on their respective centers, but at other locations, only the fractional part is added to each bin. Using Gaussians on each sample behave as an interpolation of the location of each sample around a certain value.

gaussian

private double[] gaussian

Array containing the Gaussian values corresponding to each bin for a single sample. The values of each array are updated for each sample and aggregated to the values of the bins array.

Constructor Details

HistogramMaximumLikelihoodEstimator

public HistogramMaximumLikelihoodEstimator()

Empty constructor.

HistogramMaximumLikelihoodEstimator

public HistogramMaximumLikelihoodEstimator(double gaussianSigma,
 int numberOfBins)

Constructor.

Parameters:

gaussianSigma - Gaussian sigma to be used on each sample.

numberOfBins - Number of bins to be used on the histogram.

Throws:

IllegalArgumentException - Raised if provided Gaussian sigma is negative or zero, or if provided number of bins is smaller than the minimum allowed number of bins.

HistogramMaximumLikelihoodEstimator

public HistogramMaximumLikelihoodEstimator(double[] inputData,
 double gaussianSigma,
 int numberOfBins)

Constructor.

Parameters:

inputData - Array containing input data where most likely value must be estimated from.

gaussianSigma - Gaussian sigma to be used on each sample.

numberOfBins - Number of bins to be used on the histogram.

Throws:

IllegalArgumentException - Raised if provided Gaussian sigma is negative or zero, or if provided number of bins is smaller than the minimum allowed number of bins.

HistogramMaximumLikelihoodEstimator

public HistogramMaximumLikelihoodEstimator(double minValue,
 double maxValue,
 double[] inputData,
 double gaussianSigma,
 int numberOfBins)

Constructor.

Parameters:

minValue - Minimum value assumed to be contained within input data array.

maxValue - Maximum value assumed to be contained within input data array.

inputData - Array containing input data where most likely value must be estimated from.

gaussianSigma - Gaussian sigma to be used on each sample.

numberOfBins - Number of bins to be used on the histogram.

Throws:

IllegalArgumentException - Raised if provided Gaussian sigma is negative or zero, or if provided number of bins is smaller than the minimum allowed number of bins or if minValue < maxValue.

Method Details

getMethod

public MaximumLikelihoodEstimatorMethod getMethod()

Returns method to be used for maximum likelihood estimation, which for this class is MaximumLikelihoodEstimatorMethod. HISTOGRAM_MAXIMUM_LIKELIHOOD_ESTIMATOR.

Specified by:

getMethod in class MaximumLikelihoodEstimator

Returns:

Method for maximum likelihood estimation.

getNumberOfBins

public int getNumberOfBins()

Returns number of bins to be used on the histogram. The larger the value the more precise results will be but more data will be needed to obtain statistically meaningful data so that enough samples are present on each bin.

Returns:

Number of bins to be used on the histogram.

setNumberOfBins

public void setNumberOfBins(int numberOfBins)
                     throws LockedException

Sets number of bins to be used on the histogram. The larger the provided value being set the more precise results will be but more data will be needed to obtain statistically meaningful data so that enough samples are present on each bin.

Parameters:

numberOfBins - Number of bins to be used on the histogram.

Throws:

LockedException - Exception raised if this instance is locked. This method can only be executed when computations finish and this instance becomes unlocked.

IllegalArgumentException - Raised if provided value is lower than the allowed minimum.

estimate

public double estimate()
                throws LockedException,
NotReadyException

Starts the estimation of the most likely value contained within provided input data array.

Specified by:

estimate in class MaximumLikelihoodEstimator

Returns:

The most likely value.

Throws:

LockedException - Exception raised if this instance is locked. This method can only be executed when computations finish and this instance becomes unlocked.

NotReadyException - Exception raised if this instance is not yet ready.

See Also:

• MaximumLikelihoodEstimator.isReady()

computeGaussian

protected void computeGaussian(double[] gaussian,
 double centerPos)

Internal method to compute values of Gaussian vector assumed to be centered at provided value. Gaussian values are stored in provided array so that array can be reused.

Parameters:

gaussian - Array containing Gaussian values

centerPos - Value where Gaussian is centered

internalSetNumberOfBins

private void internalSetNumberOfBins(int numberOfBins)

Internal method to set number of bins to be used on the histogram. The larger the value being set the more precise results will be but more data will be needed to obtain statistically meaningful data so that enough samples are present on each bin.

Parameters:

numberOfBins - Number of bins to be used on the histogram.

Throws:

IllegalArgumentException - Raised if provided value is lower than the allowed minimum.