Uses of Class
adams.data.statistics.AbstractArrayStatistic

Packages that use AbstractArrayStatistic

Package	Description
adams.data.spreadsheet.colstatistic
adams.data.spreadsheet.rowscore
adams.data.spreadsheet.rowstatistic
adams.data.statistics
adams.flow.transformer

Uses of AbstractArrayStatistic in adams.data.spreadsheet.colstatistic

Fields in adams.data.spreadsheet.colstatistic declared as AbstractArrayStatistic

Modifier and Type	Field	Description
protected AbstractArrayStatistic	ArrayStatistic.m_Statistic	the array statistic to use.

Methods in adams.data.spreadsheet.colstatistic that return AbstractArrayStatistic

Modifier and Type	Method	Description
AbstractArrayStatistic	ArrayStatistic.getStatistic()	Returns the array statistic to apply.

Methods in adams.data.spreadsheet.colstatistic with parameters of type AbstractArrayStatistic

Modifier and Type	Method	Description
void	ArrayStatistic.setStatistic(AbstractArrayStatistic value)	Sets the array statistic to apply.

Uses of AbstractArrayStatistic in adams.data.spreadsheet.rowscore

Fields in adams.data.spreadsheet.rowscore declared as AbstractArrayStatistic

Modifier and Type	Field	Description
protected AbstractArrayStatistic	ArrayStatistic.m_Statistic	the row statistic to use.

Methods in adams.data.spreadsheet.rowscore that return AbstractArrayStatistic

Modifier and Type	Method	Description
AbstractArrayStatistic	ArrayStatistic.getStatistic()	Returns the row statistic in use.

Methods in adams.data.spreadsheet.rowscore with parameters of type AbstractArrayStatistic

Modifier and Type	Method	Description
void	ArrayStatistic.setStatistic(AbstractArrayStatistic value)	Sets the row statistic to use.

Uses of AbstractArrayStatistic in adams.data.spreadsheet.rowstatistic

Fields in adams.data.spreadsheet.rowstatistic declared as AbstractArrayStatistic

Modifier and Type	Field	Description
protected AbstractArrayStatistic	ArrayStatistic.m_Statistic	the array statistic to use.

Methods in adams.data.spreadsheet.rowstatistic that return AbstractArrayStatistic

Modifier and Type	Method	Description
AbstractArrayStatistic	ArrayStatistic.getStatistic()	Returns the array statistic to apply.

Methods in adams.data.spreadsheet.rowstatistic with parameters of type AbstractArrayStatistic

Modifier and Type	Method	Description
void	ArrayStatistic.setStatistic(AbstractArrayStatistic value)	Sets the array statistic to apply.

Uses of AbstractArrayStatistic in adams.data.statistics

Subclasses of AbstractArrayStatistic in adams.data.statistics

Modifier and Type	Class	Description
class	AbstractArrayDistance<T extends Number>	Ancestor for distance measures.
class	AbstractOptionalSampleArrayStatistic<T extends Serializable>	Abstract super class for array statistics that can interprete the arrays either as samples or populations.
class	ArrayAndrewsCurves<T extends Number>	Generates Andrews Curves from array data. César Ignacio García Osorio, Colin Fyfe (2003).
class	ArrayAngle<T extends Number>	Calculates the angle between the first array and the remaining arrays.
class	ArrayBinning<T extends Number>	Bins the data from given array using the specified algorithm and post-processing approach.
class	ArrayChebyshevDistance	Calculates the Chebyshev distance between the first array and the remaining arrays.
class	ArrayCorrelationCoefficient<T extends Number>	Calculates the correlation coefficient between the first array and the remaining arrays.
class	ArrayCovariance<T extends Number>	Calculates the covariance between the first array and the remaining arrays.
class	ArrayDifference<T extends Number>	Calculates the difference between the arrays.
class	ArrayEuclideanDistance	Calculates the Euclidean distance between the first array and the remaining arrays.
class	ArrayHistogram<T extends Number>	Generates a histogram from the given array. The formulas for the various width/#bin calculations can be found here: WikiPedia (2010).
class	ArrayKendallTheil<T extends Number>	Calculates the Kendall-Theil robust slope (also called Theil-Sen estimator) between the first array and the remaining arrays.
class	ArrayLength<T extends Serializable>	Determines the length of an array.
class	ArrayLinearRegression<T extends Number>	Calculates the slope and intercept of linear regression between two arrays (x and y). If more than two arrays supplied, then the linear regression is computed between the first (x) and all the other ones (y).
class	ArrayManhattanDistance	Calculates the Manhattan distance between the first array and the remaining arrays.
class	ArrayMax<T extends Number>	Determines the max value in a numeric array.
class	ArrayMean<T extends Number>	Calculates the mean for a numeric array.
class	ArrayMeanAbsoluteError<T extends Number>	Calculates the mean absolute error (MAE) between the first array (actual) and the remaining arrays (predicted).
class	ArrayMedian<T extends Number>	Calculates the median for a numeric array.
class	ArrayMin<T extends Number>	Determines the min value in a numeric array.
class	ArrayMinkowskiDistance	Calculates the Minkowski distance between the first array and the remaining arrays.
class	ArrayNormalize<T extends Number>	Normalizes the array(s), i.e., the sum of its/their values is 1.0.
class	ArrayNormalizeRange<T extends Number>	Normalizes the array(s) to the specified lower and upper bound.
class	ArrayPercentile<T extends Number>	Determines the percentile for an array.
class	ArrayRelativeAbsoluteError<T extends Number>	Calculates the relative absolute error (RAE) between the first array (actual) and the remaining arrays (predicted).
class	ArrayRootMeanSquaredError<T extends Number>	Calculates the root mean squared error (RMSE) between the first array (actual) and the remaining arrays (predicted).
class	ArrayRootRelativeSquaredError<T extends Number>	Calculates the root relative squared error (RRSE) between the first array (actual) and the remaining arrays (predicted).
class	ArrayRSquared<T extends Number>	Calculates the R^2 between the first array and the remaining arrays.
class	ArrayStandardDeviation<T extends Number>	Calculates the standard deviation for a numeric array.
class	ArrayStandardize<T extends Number>	Standardizes the values in the array(s) to have mean 0 and stdev 1.
class	ArrayStandardScores<T extends Number>	Calculates the standard scores (or z scores) of the provided arrays.The arrays must be numeric, of course.
class	ArraySum<T extends Number>	Determines the sum of all values in a numeric array.
class	MultiArrayStatistic<T extends Number>	Merges the spreadsheets generated by its sub-statistics into a single one.

Fields in adams.data.statistics declared as AbstractArrayStatistic

Modifier and Type	Field	Description
protected AbstractArrayStatistic[]	AbstractDataContainerStatistics.m_Statistics	the statistics to calculate.
protected AbstractArrayStatistic[]	MultiArrayStatistic.m_SubStatistics	the statistics to perform and merge into single spreadsheet.

Methods in adams.data.statistics that return AbstractArrayStatistic

Modifier and Type	Method	Description
static AbstractArrayStatistic	AbstractArrayStatistic.forCommandLine(String cmdline)	Instantiates the statistic from the given commandline (i.e., classname and optional options).
static AbstractArrayStatistic	AbstractArrayStatistic.forName(String classname, String[] options)	Instantiates the statistic with the given options.
AbstractArrayStatistic[]	AbstractDataContainerStatistics.getStatistics()	Returns the statistics to use.
AbstractArrayStatistic[]	MultiArrayStatistic.getSubStatistics()	Returns the base statistics to use.
AbstractArrayStatistic	AbstractArrayStatistic.shallowCopy()	Returns a shallow copy of itself, i.e., based on the commandline options.
AbstractArrayStatistic	AbstractArrayStatistic.shallowCopy(boolean expand)	Returns a shallow copy of itself, i.e., based on the commandline options.

Methods in adams.data.statistics with parameters of type AbstractArrayStatistic

Modifier and Type	Method	Description
void	AbstractDataContainerStatistics.setStatistics(AbstractArrayStatistic[] value)	Sets the statistics to use.
void	MultiArrayStatistic.setSubStatistics(AbstractArrayStatistic[] value)	Sets the base statistics to use.

Uses of AbstractArrayStatistic in adams.flow.transformer

Fields in adams.flow.transformer declared as AbstractArrayStatistic

Modifier and Type	Field	Description
protected AbstractArrayStatistic	ArrayStatistic.m_Statistic	the statistic to generate.
protected AbstractArrayStatistic	SpreadSheetStatistic.m_Statistic	the statistic to generate.
protected AbstractArrayStatistic	WekaInstancesStatistic.m_Statistic	the statistic to generate.

Methods in adams.flow.transformer that return AbstractArrayStatistic

Modifier and Type	Method	Description
AbstractArrayStatistic	ArrayStatistic.getStatistic()	Returns the statistic in use.
AbstractArrayStatistic	SpreadSheetStatistic.getStatistic()	Returns the statistic in use.
AbstractArrayStatistic	WekaInstancesStatistic.getStatistic()	Returns the statistic in use.

Methods in adams.flow.transformer with parameters of type AbstractArrayStatistic

Modifier and Type	Method	Description
void	ArrayStatistic.setStatistic(AbstractArrayStatistic value)	Sets the statistic to use.
void	SpreadSheetStatistic.setStatistic(AbstractArrayStatistic value)	Sets the statistic to use.
void	WekaInstancesStatistic.setStatistic(AbstractArrayStatistic value)	Sets the statistic to use.