A B C D E F G H I M N O P R S T W

A

AbstractBuilder - Class in net.sourceforge.openforecast.input

Defines an abstract Builder class that provides some common functionality and helper methods for use by sub-classes.

AbstractBuilder() - Constructor for class net.sourceforge.openforecast.input.AbstractBuilder

AbstractForecastingModel - Class in net.sourceforge.openforecast.models

This class implements a variety of methods that are common across all forecasting models.

AbstractForecastingModel() - Constructor for class net.sourceforge.openforecast.models.AbstractForecastingModel

Default constructor.

AbstractTimeBasedModel - Class in net.sourceforge.openforecast.models

A time based forecasting model is the base class that implements much of the common code for models based on a time series.

AbstractTimeBasedModel() - Constructor for class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Constructs a new time based forecasting model.

AbstractTimeBasedModel(String) - Constructor for class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Deprecated. As of 0.4, replaced by AbstractTimeBasedModel.AbstractTimeBasedModel(java.lang.String).

accuracyIndicators - Variable in class net.sourceforge.openforecast.models.AbstractForecastingModel

The accuracy indicators, or measures of accuracy, obtained by applying this forecasting model to the initial data set.

add(DataPoint) - Method in class net.sourceforge.openforecast.DataSet

Adds the given data point object to this data set.

addAll(Collection<? extends DataPoint>) - Method in class net.sourceforge.openforecast.DataSet

Adds a collection of data points to this data set.

addVariable(String) - Method in class net.sourceforge.openforecast.input.AbstractBuilder

Adds the variable name to the end of the list of variables currently defined for this Builder.

AIC - Static variable in class net.sourceforge.openforecast.EvaluationCriteria

EvaluationCriteria referring to the Akaike Information Criteria measure.

B

BIAS - Static variable in class net.sourceforge.openforecast.EvaluationCriteria

EvaluationCriteria referring to Bias.

BLEND - Static variable in class net.sourceforge.openforecast.EvaluationCriteria

EvaluationCriteria referring to a reasonable blend of all other evaluation criteria.

build() - Method in interface net.sourceforge.openforecast.input.Builder

Retrieves a DataSet - a collection of DataPoints - from the current input source.

build() - Method in class net.sourceforge.openforecast.input.CSVBuilder

Retrieves a DataSet - a collection of DataPoints - from the current input source.

build() - Method in class net.sourceforge.openforecast.input.ResultSetBuilder

Retrieves a DataSet - a collection of DataPoints - from the current input source.

build() - Method in class net.sourceforge.openforecast.input.TimeSeriesBuilder

Retrieves a DataSet - a collection of DataPoints - from the current (JFreeChart) TimeSeries.

Builder - Interface in net.sourceforge.openforecast.input

An interface that defines the minimal requirements for a class to be considered a "builder".

C

calculateAccuracyIndicators(DataSet) - Method in class net.sourceforge.openforecast.models.AbstractForecastingModel

A helper method to calculate the various accuracy indicators when applying the given DataSet to the current forecasting model.

calculateAccuracyIndicators(DataSet) - Method in class net.sourceforge.openforecast.models.DoubleExponentialSmoothingModel

Since this version of double exponential smoothing uses the current observation to calculate a smoothed value, we must override the calculation of the accuracy indicators.

calculateAccuracyIndicators(DataSet) - Method in class net.sourceforge.openforecast.models.TripleExponentialSmoothingModel

Since this version of triple exponential smoothing uses the current observation to calculate a smoothed value, we must override the calculation of the accuracy indicators.

clear() - Method in class net.sourceforge.openforecast.DataSet

Removes all of the data points from this data set.

close() - Method in class net.sourceforge.openforecast.output.DelimitedTextOutputter

Close the DelimitedTextOutputter, flushing it first.

contains(Object) - Method in class net.sourceforge.openforecast.DataSet

Returns true if this data set contains the given data point object; or false otherwise.

containsAll(Collection<?>) - Method in class net.sourceforge.openforecast.DataSet

Returns true if this DataSet contains all of the DataPoints in the specified collection.

CSVBuilder - Class in net.sourceforge.openforecast.input

Defines a Builder that can be used to construct a DataSet from CSV (Comma Separated Values) file or input stream.

CSVBuilder(String) - Constructor for class net.sourceforge.openforecast.input.CSVBuilder

Constructs a new CSVBuilder that reads its input from the named file.

CSVBuilder(String, boolean) - Constructor for class net.sourceforge.openforecast.input.CSVBuilder

Constructs a new CSVBuilder that reads its input from the named file, and treats the first row of data as a header row containing field names.

CSVBuilder(File) - Constructor for class net.sourceforge.openforecast.input.CSVBuilder

Constructs a new CSVBuilder that reads its input from the named file.

CSVBuilder(File, boolean) - Constructor for class net.sourceforge.openforecast.input.CSVBuilder

Constructs a new CSVBuilder that reads its input from the named file.

CSVBuilder(FileReader) - Constructor for class net.sourceforge.openforecast.input.CSVBuilder

Constructs a new CSVBuilder that reads its input from the named file input stream.

CSVBuilder(FileReader, boolean) - Constructor for class net.sourceforge.openforecast.input.CSVBuilder

Constructs a new CSVBuilder that reads its input from the named file input stream.

D

DataPoint - Interface in net.sourceforge.openforecast

Defines the interface to a single data point, consisting of one value of a dependent variable, and one or more values of independent variables.

DataSet - Class in net.sourceforge.openforecast

Represents a collection of data points.

DataSet() - Constructor for class net.sourceforge.openforecast.DataSet

Constructs a new empty data set.

DataSet(DataSet) - Constructor for class net.sourceforge.openforecast.DataSet

Copy constructor: constructs a new data set object by copying the given data set.

DataSet(String, int, Collection<DataPoint>) - Constructor for class net.sourceforge.openforecast.DataSet

Constructs a new time-based data set with the named time variable, the given number of data points in a year, and the given Collection of data points.

DelimitedTextOutputter - Class in net.sourceforge.openforecast.output

Defines an Outputter that can be used to write a DataSet in any text delimited format.

DelimitedTextOutputter(String) - Constructor for class net.sourceforge.openforecast.output.DelimitedTextOutputter

Constructs a new DelimitedTextOutputter that writes its output to the named file.

DelimitedTextOutputter(String, boolean) - Constructor for class net.sourceforge.openforecast.output.DelimitedTextOutputter

Constructs a new DelimitedTextOutputter that writes its output to the named file.

DelimitedTextOutputter(File) - Constructor for class net.sourceforge.openforecast.output.DelimitedTextOutputter

Constructs a new DelimitedTextOutputter that writes its output to the given file.

DelimitedTextOutputter(File, boolean) - Constructor for class net.sourceforge.openforecast.output.DelimitedTextOutputter

Constructs a new DelimitedTextOutputter that writes its output to the given file.

DelimitedTextOutputter(Writer) - Constructor for class net.sourceforge.openforecast.output.DelimitedTextOutputter

Constructs a new DelimitedTextOutputter that writes its output to the given Writer object.

DoubleExponentialSmoothingModel - Class in net.sourceforge.openforecast.models

Double exponential smoothing - also known as Holt exponential smoothing - is a refinement of the popular simple exponential smoothing model but adds another component which takes into account any trend in the data.

DoubleExponentialSmoothingModel(double, double) - Constructor for class net.sourceforge.openforecast.models.DoubleExponentialSmoothingModel

Constructs a new double exponential smoothing forecasting model, using the given smoothing constants - alpha and gamma.

E

equals(DataPoint) - Method in interface net.sourceforge.openforecast.DataPoint

Compares the given DataPoint object to the current DataPoint object, and returns true if, and only if, the two data points represent the same data point.

equals(Object) - Method in class net.sourceforge.openforecast.DataSet

Indicates whether some other object, obj, is "equal to" this one.

equals(DataSet) - Method in class net.sourceforge.openforecast.DataSet

Indicates whether some other DataSet is "equal to" this one.

equals(Object) - Method in class net.sourceforge.openforecast.EvaluationCriteria

Compares two EvaluationCriteria objects for equality.

equals(DataPoint) - Method in class net.sourceforge.openforecast.Observation

Compares the given DataPoint to the current DataPoint/Observation, and returns true if, and only if, the two data points represent the same data point.

EvaluationCriteria - Class in net.sourceforge.openforecast

A class of constants defining the various "evaluation criteria" that can be used to compare the accuracy of two forecasting models.

F

forecast(DataPoint) - Method in interface net.sourceforge.openforecast.ForecastingModel

Using the current model parameters (initialized in init), apply the forecast model to the given data point.

forecast(DataSet) - Method in interface net.sourceforge.openforecast.ForecastingModel

Using the current model parameters (initialized in init), apply the forecast model to the given data set.

forecast(DataSet) - Method in class net.sourceforge.openforecast.models.AbstractForecastingModel

Using the current model parameters (initialized in init), apply the forecast model to the given data set.

forecast(DataPoint) - Method in class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Using the current model parameters (initialized in init), apply the forecast model to the given data point.

forecast(double) - Method in class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Returns the forecast value of the dependent variable for the given value of the independent time variable.

forecast(double) - Method in class net.sourceforge.openforecast.models.DoubleExponentialSmoothingModel

Returns the forecast value of the dependent variable for the given value of the (independent) time variable using a single exponential smoothing model.

forecast(DataPoint) - Method in class net.sourceforge.openforecast.models.MultipleLinearRegressionModel

Using the current model parameters (initialized in init), apply the forecast model to the given data point.

forecast(DataPoint) - Method in class net.sourceforge.openforecast.models.PolynomialRegressionModel

Using the current model parameters (initialized in init), apply the forecast model to the given data point.

forecast(DataPoint) - Method in class net.sourceforge.openforecast.models.RegressionModel

Using the current model parameters (initialized in init), apply the forecast model to the given data point.

forecast(double) - Method in class net.sourceforge.openforecast.models.SimpleExponentialSmoothingModel

Returns the forecast value of the dependent variable for the given value of the independent time variable using a single exponential smoothing model.

forecast(double) - Method in class net.sourceforge.openforecast.models.TripleExponentialSmoothingModel

Returns the forecast value of the dependent variable for the given value of the (independent) time variable using a single exponential smoothing model.

forecast(double) - Method in class net.sourceforge.openforecast.models.WeightedMovingAverageModel

Returns the forecast value of the dependent variable for the given value of the independent time variable.

Forecaster - Class in net.sourceforge.openforecast

The Forecaster class is a factory class that obtains the best ForecastingModel for the given data set.

ForecastingModel - Interface in net.sourceforge.openforecast

Defines a consistent interface that must be implemented by all Forecasting Models.

G

getAIC() - Method in interface net.sourceforge.openforecast.ForecastingModel

Returns the Akaike Information Criteria obtained from applying the current forecasting model to the initial data set to try and predict each data point.

getAIC() - Method in class net.sourceforge.openforecast.models.AbstractForecastingModel

Returns the Akaike Information Criteria obtained from applying the current forecasting model to the initial data set to try and predict each data point.

getAlpha() - Method in class net.sourceforge.openforecast.models.DoubleExponentialSmoothingModel

Returns the value of the smoothing constant, alpha, used in this model.

getAlpha() - Method in class net.sourceforge.openforecast.models.SimpleExponentialSmoothingModel

Returns the value of the smoothing constant, alpha, used in this model.

getAlpha() - Method in class net.sourceforge.openforecast.models.TripleExponentialSmoothingModel

Returns the value of the smoothing constant, alpha, used in this model.

getBestFitModel(DataSet) - Static method in class net.sourceforge.openforecast.models.DoubleExponentialSmoothingModel

Factory method that returns a "best fit" double exponential smoothing model for the given data set.

getBestFitModel(DataSet, double, double) - Static method in class net.sourceforge.openforecast.models.DoubleExponentialSmoothingModel

Factory method that returns a best fit double exponential smoothing model for the given data set.

getBestFitModel(DataSet) - Static method in class net.sourceforge.openforecast.models.SimpleExponentialSmoothingModel

Factory method that returns a "best fit" simple exponential smoothing model for the given data set.

getBestFitModel(DataSet, double) - Static method in class net.sourceforge.openforecast.models.SimpleExponentialSmoothingModel

Factory method that returns a best fit simple exponential smoothing model for the given data set.

getBestFitModel(DataSet) - Static method in class net.sourceforge.openforecast.models.TripleExponentialSmoothingModel

Factory method that returns a "best fit" triple exponential smoothing model for the given data set.

getBestFitModel(DataSet, double, double) - Static method in class net.sourceforge.openforecast.models.TripleExponentialSmoothingModel

Factory method that returns a best fit triple exponential smoothing model for the given data set.

getBestForecast(DataSet) - Static method in class net.sourceforge.openforecast.Forecaster

Obtains the best forecasting model for the given DataSet.

getBestForecast(DataSet, EvaluationCriteria) - Static method in class net.sourceforge.openforecast.Forecaster

Obtains the best forecasting model for the given DataSet.

getBeta() - Method in class net.sourceforge.openforecast.models.TripleExponentialSmoothingModel

Returns the value of the trend smoothing constant, beta, used in this model.

getBias() - Method in interface net.sourceforge.openforecast.ForecastingModel

Returns the bias - the arithmetic mean of the errors - obtained from applying the current forecasting model to the initial data set to try and predict each data point.

getBias() - Method in class net.sourceforge.openforecast.models.AbstractForecastingModel

Returns the bias - the arithmetic mean of the errors - obtained from applying the current forecasting model to the initial data set to try and predict each data point.

getCoefficients() - Method in class net.sourceforge.openforecast.models.MultipleLinearRegressionModel

Returns a Hashtable containing the coefficients that will be used by the current model.

getDelimiter() - Method in class net.sourceforge.openforecast.output.DelimitedTextOutputter

Returns the current field delimiter.

getDependentValue() - Method in interface net.sourceforge.openforecast.DataPoint

Returns the current value assigned to the dependent variable.

getDependentValue() - Method in class net.sourceforge.openforecast.Observation

Returns the current value assigned to the dependent variable.

getDependentVariableName() - Method in class net.sourceforge.openforecast.output.DelimitedTextOutputter

Returns the current name to be used as the dependent variable name when outputting a header row.

getForecastType() - Method in interface net.sourceforge.openforecast.ForecastingModel

Returns a one or two word name of this type of forecasting model.

getForecastType() - Method in class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Returns a one or two word name of this type of forecasting model.

getForecastType() - Method in class net.sourceforge.openforecast.models.DoubleExponentialSmoothingModel

Returns a one or two word name of this type of forecasting model.

getForecastType() - Method in class net.sourceforge.openforecast.models.MovingAverageModel

Returns a one or two word name of this type of forecasting model.

getForecastType() - Method in class net.sourceforge.openforecast.models.MultipleLinearRegressionModel

Returns a short name for this type of forecasting model.

getForecastType() - Method in class net.sourceforge.openforecast.models.NaiveForecastingModel

Returns a one or two word name of this type of forecasting model.

getForecastType() - Method in class net.sourceforge.openforecast.models.PolynomialRegressionModel

Returns a short name for this type of forecasting model.

getForecastType() - Method in class net.sourceforge.openforecast.models.RegressionModel

Returns a short name for this type of forecasting model.

getForecastType() - Method in class net.sourceforge.openforecast.models.SimpleExponentialSmoothingModel

Returns a one or two word name of this type of forecasting model.

getForecastType() - Method in class net.sourceforge.openforecast.models.TripleExponentialSmoothingModel

Returns a one or two word name of this type of forecasting model.

getForecastType() - Method in class net.sourceforge.openforecast.models.WeightedMovingAverageModel

Returns a one or two word name of this type of forecasting model.

getForecastValue(double) - Method in class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Returns the forecast value for the dependent variable for the given value of the independent time variable.

getGamma() - Method in class net.sourceforge.openforecast.models.DoubleExponentialSmoothingModel

Returns the value of the trend smoothing constant, gamma, used in this model.

getGamma() - Method in class net.sourceforge.openforecast.models.TripleExponentialSmoothingModel

Returns the value of the seasonal smoothing constant, gamma, used in this model.

getIndependentValue(String) - Method in interface net.sourceforge.openforecast.DataPoint

Returns the current value assigned to the named independent variable.

getIndependentValue(String) - Method in class net.sourceforge.openforecast.Observation

Returns the current value assigned to the named independent variable.

getIndependentVariable() - Method in class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Returns the independent variable - or the time variable - used in this model.

getIndependentVariableNames() - Method in interface net.sourceforge.openforecast.DataPoint

Returns an array of all independent variable names.

getIndependentVariableNames() - Method in class net.sourceforge.openforecast.Observation

Returns an array of all independent variable names.

getIndependentVariables() - Method in class net.sourceforge.openforecast.DataSet

Returns an ordered array of all independent variable names used in this data set.

getIntercept() - Method in class net.sourceforge.openforecast.models.MultipleLinearRegressionModel

Returns the intercept that will be used by the current model.

getMAD() - Method in interface net.sourceforge.openforecast.ForecastingModel

Returns the mean absolute deviation obtained from applying the current forecasting model to the initial data set to try and predict each data point.

getMAD() - Method in class net.sourceforge.openforecast.models.AbstractForecastingModel

Returns the mean absolute deviation obtained from applying the current forecasting model to the initial data set to try and predict each data point.

getMAPE() - Method in interface net.sourceforge.openforecast.ForecastingModel

Returns the mean absolute percentage error obtained from applying the current forecasting model to the initial data set to try and predict each data point.

getMAPE() - Method in class net.sourceforge.openforecast.models.AbstractForecastingModel

Returns the mean absolute percentage error obtained from applying the current forecasting model to the initial data set to try and predict each data point.

getMaximumTimeValue() - Method in class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Returns the maximum value of the independent time variable currently forecast by this model.

getMinimumTimeValue() - Method in class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Returns the minimum value of the independent time variable currently forecast by this model.

getMSE() - Method in interface net.sourceforge.openforecast.ForecastingModel

Returns the mean square of the errors (MSE) obtained from applying the current forecasting model to the initial data set to try and predict each data point.

getMSE() - Method in class net.sourceforge.openforecast.models.AbstractForecastingModel

Returns the mean square of the errors (MSE) obtained from applying the current forecasting model to the initial data set to try and predict each data point.

getNumberOfPeriods() - Method in class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Returns the current number of periods used in this model.

getNumberOfPeriods() - Method in class net.sourceforge.openforecast.models.DoubleExponentialSmoothingModel

Returns the current number of periods used in this model.

getNumberOfPeriods() - Method in class net.sourceforge.openforecast.models.SimpleExponentialSmoothingModel

Returns the current number of periods used in this model.

getNumberOfPeriods() - Method in class net.sourceforge.openforecast.models.TripleExponentialSmoothingModel

Returns the current number of periods used in this model.

getNumberOfPeriods() - Method in class net.sourceforge.openforecast.models.WeightedMovingAverageModel

Returns the current number of periods used in this model.

getNumberOfPredictors() - Method in interface net.sourceforge.openforecast.ForecastingModel

Returns the number of predictors used by the underlying model.

getNumberOfPredictors() - Method in class net.sourceforge.openforecast.models.DoubleExponentialSmoothingModel

Returns the number of predictors used by the underlying model.

getNumberOfPredictors() - Method in class net.sourceforge.openforecast.models.MultipleLinearRegressionModel

Returns the number of predictors used by the underlying model.

getNumberOfPredictors() - Method in class net.sourceforge.openforecast.models.PolynomialRegressionModel

Returns the number of predictors used by the underlying model.

getNumberOfPredictors() - Method in class net.sourceforge.openforecast.models.RegressionModel

Returns the number of predictors used by the underlying model.

getNumberOfPredictors() - Method in class net.sourceforge.openforecast.models.SimpleExponentialSmoothingModel

Returns the number of predictors used by the underlying model.

getNumberOfPredictors() - Method in class net.sourceforge.openforecast.models.TripleExponentialSmoothingModel

Returns the number of predictors used by the underlying model.

getNumberOfPredictors() - Method in class net.sourceforge.openforecast.models.WeightedMovingAverageModel

Returns the number of predictors used by the underlying model.

getNumberOfVariables() - Method in class net.sourceforge.openforecast.input.AbstractBuilder

Returns the number of variables currently defined in this AbstractBuilder.

getObservedValue(double) - Method in class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Returns the observed value of the dependent variable for the given value of the independent time variable.

getPeriodsPerYear() - Method in class net.sourceforge.openforecast.DataSet

Returns the number of periods - or data points - in a years worth of data for time-series data.

getSAE() - Method in interface net.sourceforge.openforecast.ForecastingModel

Returns the sum of the absolute errors (SAE) obtained from applying the current forecasting model to the initial data set to try and predict each data point.

getSAE() - Method in class net.sourceforge.openforecast.models.AbstractForecastingModel

Returns the Sum of Absolute Errors (SAE) obtained by applying the current forecasting model to the initial data set.

getTimeInterval() - Method in class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Returns the current time interval between observations.

getTimeVariable() - Method in class net.sourceforge.openforecast.DataSet

Returns the time variable associated with this data set, or null if no time variable has been defined.

getTimeVariable() - Method in class net.sourceforge.openforecast.input.TimeSeriesBuilder

Returns the name of the currently defined time variable.

getTimeVariable() - Method in class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Returns the name of the independent variable representing the time value used by this model.

getVariableName(int) - Method in class net.sourceforge.openforecast.input.AbstractBuilder

Returns the variable name with the given index.

H

hashCode() - Method in class net.sourceforge.openforecast.DataSet

Returns the hash code value for this collection, based on the underlying Collection of DataPoints.

HUNTER - Static variable in class net.sourceforge.openforecast.models.SimpleExponentialSmoothingModel

Used in the three argument constructor to specify that Hunter's formula is to be used for calculating forecast values.

I

init(DataSet) - Method in interface net.sourceforge.openforecast.ForecastingModel

Used to initialize the model-specific parameters and customize them to the given data set.

init(DataSet) - Method in class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Used to initialize the time based model.

init(DataSet) - Method in class net.sourceforge.openforecast.models.MovingAverageModel

Used to initialize the moving average model.

init(DataSet) - Method in class net.sourceforge.openforecast.models.MultipleLinearRegressionModel

Initializes the coefficients to use for this regression model.

init(double, Hashtable<String, Double>) - Method in class net.sourceforge.openforecast.models.MultipleLinearRegressionModel

Initializes the coefficients to use for this regression model with the given values.

init(DataSet) - Method in class net.sourceforge.openforecast.models.PolynomialRegressionModel

Initializes the coefficients to use for this regression model.

init(DataSet) - Method in class net.sourceforge.openforecast.models.RegressionModel

Initializes the coefficients to use for this regression model.

init(DataSet) - Method in class net.sourceforge.openforecast.models.TripleExponentialSmoothingModel

Used to initialize the time based model.

initialized - Variable in class net.sourceforge.openforecast.models.AbstractForecastingModel

Remembers whether this model has been properly initialized.

initTimeVariable(DataSet) - Method in class net.sourceforge.openforecast.models.AbstractTimeBasedModel

Initializes the time variable from the given data set.

InsufficientDataException - Exception in net.sourceforge.openforecast.models

Represents the case when there is insufficient data available to return a valid forecast value.

InsufficientDataException() - Constructor for exception net.sourceforge.openforecast.models.InsufficientDataException

Default constructor.

InsufficientDataException(String) - Constructor for exception net.sourceforge.openforecast.models.InsufficientDataException

Constructs a new InsufficientDataException with the given reason.

isEmpty() - Method in class net.sourceforge.openforecast.DataSet

Returns true if this data set contains no data points.

iterator() - Method in class net.sourceforge.openforecast.DataSet

Returns an iterator over the data points in this data set.

M

MAD - Static variable in class net.sourceforge.openforecast.EvaluationCriteria

EvaluationCriteria referring to the Mean Absolute Deviation.

MAPE - Static variable in class net.sourceforge.openforecast.EvaluationCriteria

EvaluationCriteria referring to the Mean Absolute Percentage Error.

ModelNotInitializedException - Exception in net.sourceforge.openforecast.models

This exception should be thrown when an attempt is made to use a method in a model that has not been initialized by calling init.

ModelNotInitializedException() - Constructor for exception net.sourceforge.openforecast.models.ModelNotInitializedException

Constructs a new ModelNotInitializedException with no detail message.

ModelNotInitializedException(String) - Constructor for exception net.sourceforge.openforecast.models.ModelNotInitializedException

Constructs a new ModelNotInitializedException with the specified detail message.

MovingAverageModel - Class in net.sourceforge.openforecast.models

A moving average forecast model is based on an artificially constructed time series in which the value for a given time period is replaced by the mean of that value and the values for some number of preceding and succeeding time periods.

MovingAverageModel() - Constructor for class net.sourceforge.openforecast.models.MovingAverageModel

Constructs a new moving average forecasting model.

MovingAverageModel(String) - Constructor for class net.sourceforge.openforecast.models.MovingAverageModel

Deprecated. As of 0.4, replaced by MovingAverageModel.MovingAverageModel(java.lang.String, int).

MovingAverageModel(int) - Constructor for class net.sourceforge.openforecast.models.MovingAverageModel

Constructs a new moving average forecasting model, using the specified period.

MovingAverageModel(String, int) - Constructor for class net.sourceforge.openforecast.models.MovingAverageModel

Deprecated. As of 0.4, replaced by MovingAverageModel.MovingAverageModel(int).

MSE - Static variable in class net.sourceforge.openforecast.EvaluationCriteria

EvaluationCriteria referring to the Mean Squared Error.

MultipleLinearRegressionModel - Class in net.sourceforge.openforecast.models

Implements a multiple variable linear regression model using the variables named in the constructor as the independent variables, or the variables passed into one of the init methods.

MultipleLinearRegressionModel() - Constructor for class net.sourceforge.openforecast.models.MultipleLinearRegressionModel

A default constructor that constructs a new multiple variable Linear regression model.

MultipleLinearRegressionModel(String[]) - Constructor for class net.sourceforge.openforecast.models.MultipleLinearRegressionModel

Constructs a new multiple variable linear regression model, using the given array of names as the independent variables to use.

N

NaiveForecastingModel - Class in net.sourceforge.openforecast.models

A naive forecasting model is a special case of the moving average forecasting model where the number of periods used for smoothing is 1.

NaiveForecastingModel() - Constructor for class net.sourceforge.openforecast.models.NaiveForecastingModel

Constructs a new naive forecasting model.

NaiveForecastingModel(String) - Constructor for class net.sourceforge.openforecast.models.NaiveForecastingModel

Deprecated. As of 0.4, replaced by NaiveForecastingModel.NaiveForecastingModel(java.lang.String).

net.sourceforge.openforecast - package net.sourceforge.openforecast

This is the main package for OpenForecast.

net.sourceforge.openforecast.input - package net.sourceforge.openforecast.input

Defines a variety of helper classes used for creating DataSet and DataPoint objects from a variety of different input sources.

net.sourceforge.openforecast.models - package net.sourceforge.openforecast.models

Defines the different ForecastingModels implemented in OpenForecast.

net.sourceforge.openforecast.output - package net.sourceforge.openforecast.output

Defines a variety of helper classes used for outputting DataSet and DataPoint objects to a variety of different output sources.

O

Observation - Class in net.sourceforge.openforecast

Represents a single observation or data point, consisting of one value of a dependent variable, and one or more values of independent variables.

Observation(double) - Constructor for class net.sourceforge.openforecast.Observation

Initializes the current Observation with the given value of the dependent variable.

Observation(DataPoint) - Constructor for class net.sourceforge.openforecast.Observation

Like a copy constructor, but constructs a new Observation object by making a copy of the values from the given data point.

output(DataSet) - Method in class net.sourceforge.openforecast.output.DelimitedTextOutputter

Writes a DataSet - a collection of DataPoints - to the current writer.

output(DataPoint) - Method in class net.sourceforge.openforecast.output.DelimitedTextOutputter

Outputs the given DataPoint to the current Writer.

output(DataSet) - Method in interface net.sourceforge.openforecast.output.Outputter

Outputs the DataSet - a collection of DataPoints - to the current output destination.

output(DataSet) - Method in class net.sourceforge.openforecast.output.TimeSeriesOutputter

Adds a DataSet - a collection of DataPoints - to the current TimeSeries.

Outputter - Interface in net.sourceforge.openforecast.output

An interface that defines the minimal requirements for a class to be considered an "outputter" - a class that can be used to assist with the output of a DataSet (set of DataPoint objects) to a variety of different output destinations.

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PolynomialRegressionModel - Class in net.sourceforge.openforecast.models

Implements a single variable polynomial regression model using the variable named in the constructor as the independent variable.

PolynomialRegressionModel(String) - Constructor for class net.sourceforge.openforecast.models.PolynomialRegressionModel

Constructs a new polynomial regression model, using the given name as the independent variable.

PolynomialRegressionModel(String, int) - Constructor for class net.sourceforge.openforecast.models.PolynomialRegressionModel

Constructs a new linear regression model, using the given name as the independent variable.

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RegressionModel - Class in net.sourceforge.openforecast.models

Implements a single variable linear regression model using the variable named in the constructor as the independent variable.

RegressionModel(String) - Constructor for class net.sourceforge.openforecast.models.RegressionModel

Constructs a new linear regression model, using the given name as the independent variable.

remove(Object) - Method in class net.sourceforge.openforecast.DataSet

Removes a single instance of the specified data point object from this data set, if it is present.

removeAll(Collection<?>) - Method in class net.sourceforge.openforecast.DataSet

Not currently implemented - always throws UnsupportedOperationException.

ResultSetBuilder - Class in net.sourceforge.openforecast.input

Defines a Builder that can be used to construct a DataSet from a ResultSet.

ResultSetBuilder(ResultSet) - Constructor for class net.sourceforge.openforecast.input.ResultSetBuilder

Constructs a new ResultSetBuilder that reads its input from the given ResultSet.

retainAll(Collection<?>) - Method in class net.sourceforge.openforecast.DataSet

Not currently implemented - always throws UnsupportedOperationException.

ROBERTS - Static variable in class net.sourceforge.openforecast.models.SimpleExponentialSmoothingModel

Used in the three argument constructor to specify that Robert's formula is to be used for calculating forecast values.

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SAE - Static variable in class net.sourceforge.openforecast.EvaluationCriteria

EvaluationCriteria referring to the Sum of the Absolute Error.

setDelimiter(String) - Method in class net.sourceforge.openforecast.output.DelimitedTextOutputter

Sets the field delimiter to the given String.

setDependentValue(double) - Method in interface net.sourceforge.openforecast.DataPoint

Sets the dependent variables' value to the given value.

setDependentValue(double) - Method in class net.sourceforge.openforecast.Observation

Sets the dependent variables' value to the given value.

setDependentVariableName(String) - Method in class net.sourceforge.openforecast.output.DelimitedTextOutputter

Sets the name/label to be used as the dependent variable name when outputting a header row.

setIndependentValue(String, double) - Method in interface net.sourceforge.openforecast.DataPoint

Sets the named independent variables' value to the given value.

setIndependentValue(String, double) - Method in class net.sourceforge.openforecast.Observation

Sets the named independent variables' value to the given value.

setNumberOfVariables(int) - Method in class net.sourceforge.openforecast.input.AbstractBuilder

Sets the number of variables to be defined/referenced by this AbstractBuilder.

setOutputHeaderRow(boolean) - Method in class net.sourceforge.openforecast.output.DelimitedTextOutputter

Enables/Disables the output of the header row containing column/field names.

setPeriodsPerYear(int) - Method in class net.sourceforge.openforecast.DataSet

Sets the number of periods - or data points - in a years worth of data for time-series data.

setTimeVariable(String) - Method in class net.sourceforge.openforecast.DataSet

Sets the name of the time variable for this data set.

setTimeVariable(String) - Method in class net.sourceforge.openforecast.input.TimeSeriesBuilder

Used to change the time variable name.

setVariableName(int, String) - Method in class net.sourceforge.openforecast.input.AbstractBuilder

Sets the name for the variable with the given index to the given name.

setWeights(double[]) - Method in class net.sourceforge.openforecast.models.WeightedMovingAverageModel

Sets the weights used by this weighted moving average forecasting model to the given weights.

SimpleExponentialSmoothingModel - Class in net.sourceforge.openforecast.models

A simple exponential smoothing forecast model is a very popular model used to produce a smoothed Time Series.

SimpleExponentialSmoothingModel(double) - Constructor for class net.sourceforge.openforecast.models.SimpleExponentialSmoothingModel

Constructs a new simple exponential smoothing forecasting model, using the specified smoothing constant.

SimpleExponentialSmoothingModel(String, double) - Constructor for class net.sourceforge.openforecast.models.SimpleExponentialSmoothingModel

Deprecated. As of 0.4, replaced by SimpleExponentialSmoothingModel.SimpleExponentialSmoothingModel(double).

SimpleExponentialSmoothingModel(double, int) - Constructor for class net.sourceforge.openforecast.models.SimpleExponentialSmoothingModel

Constructs a new exponential smoothing forecasting model, using the given name as the independent variable and the specified smoothing constant.

SimpleExponentialSmoothingModel(String, double, int) - Constructor for class net.sourceforge.openforecast.models.SimpleExponentialSmoothingModel

Deprecated. As of 0.4, replaced by SimpleExponentialSmoothingModel.SimpleExponentialSmoothingModel(double,int).

size() - Method in class net.sourceforge.openforecast.DataSet

Returns the number of data points in this data set.

sort(String) - Method in class net.sourceforge.openforecast.DataSet

Sorts the given data set according to increasing value of the named independent variable.

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TimeSeriesBuilder - Class in net.sourceforge.openforecast.input

Defines a Builder that can be used to construct a DataSet from a TimeSeries object as used/defined by JFreeChart.

TimeSeriesBuilder(TimeSeries) - Constructor for class net.sourceforge.openforecast.input.TimeSeriesBuilder

Constructs a new TimeSeriesBuilder that reads its input from the given TimeSeries object.

TimeSeriesBuilder(TimeSeries, String) - Constructor for class net.sourceforge.openforecast.input.TimeSeriesBuilder

Constructs a new TimeSeriesBuilder that reads its input from the given TimeSeries object.

TimeSeriesOutputter - Class in net.sourceforge.openforecast.output

Defines an Outputter that can be used to add the DataPoints from a DataSet to a (JFreeChart) TimeSeries.

TimeSeriesOutputter(TimeSeries, Class<?>) - Constructor for class net.sourceforge.openforecast.output.TimeSeriesOutputter

Constructs a new TimeSeriesOutputter that adds its output to the named TimeSeries.

toString() - Method in class net.sourceforge.openforecast.DataSet

Overrides the default toString method.

toString() - Method in class net.sourceforge.openforecast.EvaluationCriteria

Returns a textual description of this evaluation criteria object.

toString() - Method in interface net.sourceforge.openforecast.ForecastingModel

This should be overridden to provide a textual description of the current forecasting model including, where possible, any derived parameters used.

toString() - Method in class net.sourceforge.openforecast.models.AbstractTimeBasedModel

This should be overridden to provide a textual description of the current forecasting model including, where possible, any derived parameters used.

toString() - Method in class net.sourceforge.openforecast.models.DoubleExponentialSmoothingModel

This should be overridden to provide a textual description of the current forecasting model including, where possible, any derived parameters used.

toString() - Method in class net.sourceforge.openforecast.models.MovingAverageModel

This should be overridden to provide a textual description of the current forecasting model including, where possible, any derived parameters used.

toString() - Method in class net.sourceforge.openforecast.models.MultipleLinearRegressionModel

Returns a detailed description of this forcasting model, including the intercept and slope.

toString() - Method in class net.sourceforge.openforecast.models.NaiveForecastingModel

This should be overridden to provide a textual description of the current forecasting model including, where possible, any derived parameters used.

toString() - Method in class net.sourceforge.openforecast.models.PolynomialRegressionModel

Returns a detailed description of this forcasting model, including the intercept and slope.

toString() - Method in class net.sourceforge.openforecast.models.RegressionModel

Returns a detailed description of this forcasting model, including the intercept and slope.

toString() - Method in class net.sourceforge.openforecast.models.SimpleExponentialSmoothingModel

This should be overridden to provide a textual description of the current forecasting model including, where possible, any derived parameters used.

toString() - Method in class net.sourceforge.openforecast.models.TripleExponentialSmoothingModel

This should be overridden to provide a textual description of the current forecasting model including, where possible, any derived parameters used.

toString() - Method in class net.sourceforge.openforecast.models.WeightedMovingAverageModel

This should be overridden to provide a textual description of the current forecasting model including, where possible, any derived parameters used.

toString() - Method in class net.sourceforge.openforecast.Observation

Overrides the default toString method to provide a more meaningful output of an Observation.

TripleExponentialSmoothingModel - Class in net.sourceforge.openforecast.models

Triple exponential smoothing - also known as the Winters method - is a refinement of the popular double exponential smoothing model but adds another component which takes into account any seasonality - or periodicity - in the data.

TripleExponentialSmoothingModel(double, double, double) - Constructor for class net.sourceforge.openforecast.models.TripleExponentialSmoothingModel

Constructs a new triple exponential smoothing forecasting model, using the given smoothing constants - alpha, beta and gamma.

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WeightedMovingAverageModel - Class in net.sourceforge.openforecast.models

A weighted moving average forecast model is based on an artificially constructed time series in which the value for a given time period is replaced by the weighted mean of that value and the values for some number of preceding time periods.

WeightedMovingAverageModel(double[]) - Constructor for class net.sourceforge.openforecast.models.WeightedMovingAverageModel

Constructs a new weighted moving average forecasting model, using the specified weights.

WeightedMovingAverageModel(String, double[]) - Constructor for class net.sourceforge.openforecast.models.WeightedMovingAverageModel

Deprecated. As of 0.4, replaced by WeightedMovingAverageModel.WeightedMovingAverageModel(double[]).

WeightedMovingAverageModel() - Constructor for class net.sourceforge.openforecast.models.WeightedMovingAverageModel

Constructs a new weighted moving average forecasting model.

WeightedMovingAverageModel(String) - Constructor for class net.sourceforge.openforecast.models.WeightedMovingAverageModel

Deprecated. As of 0.4, replaced by WeightedMovingAverageModel.WeightedMovingAverageModel(java.lang.String).

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