java.lang.Object
- jsl.utilities.statistic.AbstractCollector
- - jsl.utilities.statistic.AbstractStatistic
  - - jsl.utilities.statistic.StandardizedTimeSeriesStatistic

All Implemented Interfaces:

java.lang.Comparable<AbstractStatistic>, GetNameIfc, IdentityIfc, ArraySaverIfc, CollectorIfc, GetCSVStatisticIfc, StatisticAccessorIfc
```
public class StandardizedTimeSeriesStatistic
extends AbstractStatistic
```
Implements the Standardized Time Series method as described on page 534 of Law and Kelton, 3rd edition

Field Summary

Fields
Modifier and Type Field Description

static int BATCH_SIZE
the default minimum number of observations per batch, the batch size
- Fields inherited from class jsl.utilities.statistic.AbstractStatistic
  DEFAULT_CONFIDENCE_LEVEL, myConfidenceLevel, myNumMissing
- Fields inherited from interface jsl.utilities.statistic.ArraySaverIfc
  DEFAULT_DATA_ARRAY_SIZE

Constructor Summary

Constructors
Constructor	Description
`StandardizedTimeSeriesStatistic()`	Creates an STS Statistic with the default batch size = 1024 The batch means will not be saved
`StandardizedTimeSeriesStatistic(boolean saveBMFlag)`	Creates an STS Statistic with the default batch size = 1024 The batch means will not be saved
`StandardizedTimeSeriesStatistic(boolean saveBMFlag, double[] values)`	Creates an STS Statistic with the default batch size = 1024 The batch means will not be saved
`StandardizedTimeSeriesStatistic(double[] values)`	Creates an STS Statistic with the default batch size = 1024 The batch means will not be saved
`StandardizedTimeSeriesStatistic(int batchSize)`	Creates an STS Statistic with the given batchsize.
`StandardizedTimeSeriesStatistic(int batchSize, boolean saveBMFlag)`	Creates an STS Statistic with the given batch size.
`StandardizedTimeSeriesStatistic(int batchSize, boolean saveBMFlag, double[] values)`	Creates an STS Statistic with the given batch size.
`StandardizedTimeSeriesStatistic(int batchSize, boolean saveBMFlag, java.lang.String name, double[] values)`	Creates an STS Statistic with the given batch size.
`StandardizedTimeSeriesStatistic(int batchSize, double[] values)`	Creates an STS Statistic with the given batchsize.
`StandardizedTimeSeriesStatistic(int batchSize, java.lang.String name)`	Creates an STS Statistic with the given batch size and name.
`StandardizedTimeSeriesStatistic(int batchSize, java.lang.String name, double[] values)`	Creates an STS Statistic with the given batch size and name.
`StandardizedTimeSeriesStatistic(java.lang.String name)`	Creates an STS Statistic with the default batch size = 1024 The batch means will not be saved
`StandardizedTimeSeriesStatistic(java.lang.String name, double[] values)`	Creates an STS Statistic with the default batch size = 1024 The batch means will not be saved

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`void`	`collect(double value)`	Collect on the supplied value
`StatisticAccessorIfc`	`getAcrossBatchStatistic()`	Gets a StatisticAccessIfc that represents the across batch statistics
`double`	`getAverage()`	Gets the unweighted average of the observations.
`java.util.Iterator<Statistic>`	`getBatchMeansIterator()`	Returns an iterator across all the batch means collected so far
`double`	`getCount()`	Gets the count of the number of the observations.
`StatisticAccessorIfc`	`getCurrentBatchStatistic()`	Gets a StatisticAccessIfc for the current batch that is being collected.
`double`	`getDeviationSumOfSquares()`	Gets the sum of squares of the deviations from the average This is the numerator in the classic sample variance formula
`double`	`getHalfWidth(double alpha)`	Gets the confidence interval half-width.
`double`	`getKurtosis()`	Gets the kurtosis of the data
`double`	`getLag1Correlation()`	Gets the lag-1 generate correlation of the unweighted observations.
`double`	`getLag1Covariance()`	Gets the lag-1 generate covariance of the unweighted observations.
`double`	`getLastValue()`	Gets the last observed data point
`int`	`getLeadingDigitRule(double a)`	Computes the right most meaningful digit according to (int)Math.floor(Math.log10(a*getStandardError())) See doi 10.1287.opre.1080.0529 by Song and Schmeiser
`double`	`getMax()`	Gets the maximum of the observations.
`double`	`getMin()`	Gets the minimum of the observations.
`double`	`getNumBatches()`	Gets the number of batches
`double`	`getSkewness()`	Gets the skewness of the data
`double`	`getStandardDeviation()`	Gets the sample standard deviation of the observations.
`double`	`getStandardError()`	Gets the standard error of the observations.
`double`	`getSTSAreaConstant()`	Computes an estimate of the STS Area Constant
`double`	`getSTSHalfWidth()`	Computes the half-width of a STS based confidence interval based on a 95% confidence level
`double`	`getSTSHalfWidth(double level)`	Computes the half-width of a STS based confidence interval based on the supplied confidence coefficient.
`double`	`getSTSStandardError()`	Gets the standard error for the STS confidence interval
`double`	`getSum()`	Gets the sum of the observations.
`StatisticAccessorIfc`	`getUnBatchedStatistic()`	Gets a StatisticAccessorIfc that represents statistics that have been collected on each unbatched data point This is the same as using a Statistic on the data
`double`	`getVariance()`	Gets the sample variance of the observations.
`double`	`getVonNeumannLag1TestStatistic()`	Gets the Von Neumann Lag 1 test statistic for checking the hypothesis that the data are uncorrelated Note: See Handbook of Simulation, Jerry Banks editor, McGraw-Hill, pg 253.
`double`	`getVonNeumannLag1TestStatisticPValue()`	Returns the asymptotic p-value for the Von Nueumann Lag-1 Test Statistic:
`static void`	`main(java.lang.String[] args)`
`void`	`reset()`	Resets the collector as if no observations had been collected.
`protected void`	`setBatchSize(int batchSize)`	Sets the number of batches, must be >=2
`java.lang.String`	`toString()`	Returns a String representation of the Statistic

Methods inherited from class jsl.utilities.statistic.AbstractStatistic
compareTo, getConfidenceLevel, getNumberMissing, setConfidenceLevel

Methods inherited from class jsl.utilities.statistic.AbstractCollector
clearSavedData, getId, getName, getSavedData, getSaveOption, save, save, setArraySizeIncrement, setName, setSaveOption

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface jsl.utilities.statistic.CollectorIfc
collect, collect, collect

Methods inherited from interface jsl.utilities.statistic.StatisticAccessorIfc
getConfidenceInterval, getConfidenceInterval, getCSVHeader, getCSVStatistic, getCSVStatisticHeader, getCSVValues, getHalfWidth, getName, getRelativeError, getRelativeWidth, getRelativeWidth, getStatistics, getStatisticsAsMap

- Field Detail
  - BATCH_SIZE
```
public static final int BATCH_SIZE
```
    the default minimum number of observations per batch, the batch size
    
    See Also:
    
    Constant Field Values
- Constructor Detail
  - StandardizedTimeSeriesStatistic
```
public StandardizedTimeSeriesStatistic()
```
    Creates an STS Statistic with the default batch size = 1024 The batch means will not be saved
  - StandardizedTimeSeriesStatistic
```
public StandardizedTimeSeriesStatistic(java.lang.String name)
```
    Creates an STS Statistic with the default batch size = 1024 The batch means will not be saved
    
    Parameters:
    
    name - the name of the statistic
  - StandardizedTimeSeriesStatistic
```
public StandardizedTimeSeriesStatistic(boolean saveBMFlag)
```
    Creates an STS Statistic with the default batch size = 1024 The batch means will not be saved
    
    Parameters:
    
    saveBMFlag - Indicates whether or not the batch means will be saved, true means saved, false means not saved. False is the default
  - StandardizedTimeSeriesStatistic
```
public StandardizedTimeSeriesStatistic(boolean saveBMFlag,
                                       double[] values)
```
    Creates an STS Statistic with the default batch size = 1024 The batch means will not be saved
    
    Parameters:
    
    saveBMFlag - Indicates whether or not the batch means will be saved, true means saved, false means not saved. False is the default
    
    values - an array of values to collect statistics on
  - StandardizedTimeSeriesStatistic
```
public StandardizedTimeSeriesStatistic(double[] values)
```
    Creates an STS Statistic with the default batch size = 1024 The batch means will not be saved
    
    Parameters:
    
    values - an array of values to collect statistics on
  - StandardizedTimeSeriesStatistic
```
public StandardizedTimeSeriesStatistic(java.lang.String name,
                                       double[] values)
```
    Creates an STS Statistic with the default batch size = 1024 The batch means will not be saved
    
    Parameters:
    
    name - The name
    
    values - an array of values to collect statistics on
  - StandardizedTimeSeriesStatistic
```
public StandardizedTimeSeriesStatistic(int batchSize)
```
    Creates an STS Statistic with the given batchsize. The batch means will not be saved
    
    Parameters:
    
    batchSize - Must be >= 2
  - StandardizedTimeSeriesStatistic
```
public StandardizedTimeSeriesStatistic(int batchSize,
                                       double[] values)
```
    Creates an STS Statistic with the given batchsize. The batch means will not be saved
    
    Parameters:
    
    batchSize - Must be >= 2
    
    values - an array of values to collect statistics on
  - StandardizedTimeSeriesStatistic
```
public StandardizedTimeSeriesStatistic(int batchSize,
                                       java.lang.String name)
```
    Creates an STS Statistic with the given batch size and name. The batch means will not be save.
    
    Parameters:
    
    batchSize - Must be >= 2
    
    name - The name
  - StandardizedTimeSeriesStatistic
```
public StandardizedTimeSeriesStatistic(int batchSize,
                                       java.lang.String name,
                                       double[] values)
```
    Creates an STS Statistic with the given batch size and name. The batch means will not be save.
    
    Parameters:
    
    batchSize - Must be >= 2
    
    name - The name
    
    values - an array of values to collect statistics on
  - StandardizedTimeSeriesStatistic
```
public StandardizedTimeSeriesStatistic(int batchSize,
                                       boolean saveBMFlag)
```
    Creates an STS Statistic with the given batch size.
    
    Parameters:
    
    batchSize - Must be >=2
    
    saveBMFlag - Indicates whether or not the batch means will be saved, true means saved, false means not saved. False is the default
  - StandardizedTimeSeriesStatistic
```
public StandardizedTimeSeriesStatistic(int batchSize,
                                       boolean saveBMFlag,
                                       double[] values)
```
    Creates an STS Statistic with the given batch size.
    
    Parameters:
    
    batchSize - Must be >=2
    
    saveBMFlag - Indicates whether or not the batch means will be saved, true means saved, false means not saved. False is the default
    
    values - an array of values to collect statistics on
  - StandardizedTimeSeriesStatistic
```
public StandardizedTimeSeriesStatistic(int batchSize,
                                       boolean saveBMFlag,
                                       java.lang.String name,
                                       double[] values)
```
    Creates an STS Statistic with the given batch size.
    
    Parameters:
    
    batchSize - Must be >=2
    
    saveBMFlag - Indicates whether or not the batch means will be saved, true means saved, false means not saved. False is the default
    
    name - The name of the statistic
    
    values - an array of values to collect statistics on
- Method Detail
  - getNumBatches
```
public final double getNumBatches()
```
    Gets the number of batches
    
    Returns:
    
    Returns the number of batches
  - collect
```
public final void collect(double value)
```
    Description copied from interface: CollectorIfc
    
    Collect on the supplied value
    
    Parameters:
    
    value - a double representing the observation
  - reset
```
public final void reset()
```
    Description copied from interface: CollectorIfc
    
    Resets the collector as if no observations had been collected.
  - getCount
```
public final double getCount()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the count of the number of the observations.
    
    Returns:
    
    A double representing the count
  - getAverage
```
public final double getAverage()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the unweighted average of the observations.
    
    Returns:
    
    A double representing the average or Double.NaN if no observations.
  - getSum
```
public final double getSum()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the sum of the observations.
    
    Returns:
    
    A double representing the unweighted sum
  - getDeviationSumOfSquares
```
public final double getDeviationSumOfSquares()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the sum of squares of the deviations from the average This is the numerator in the classic sample variance formula
    
    Returns:
    
    A double representing the sum of squares of the deviations from the average
  - getVariance
```
public final double getVariance()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the sample variance of the observations.
    
    Returns:
    
    A double representing the generate variance or Double.NaN if 1 or less observations.
  - getStandardDeviation
```
public final double getStandardDeviation()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the sample standard deviation of the observations. Simply the square root of getVariance()
    
    Returns:
    
    A double representing the generate standard deviation or Double.NaN if 1 or less observations.
  - getHalfWidth
```
public final double getHalfWidth(double alpha)
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the confidence interval half-width. Simply the generate standard error times the confidence coefficient as determined by an appropriate sampling distribution
    
    Parameters:
    
    alpha - the confidence level
    
    Returns:
    
    A double representing the half-width or Double.NaN if < 1 observation
  - getMin
```
public final double getMin()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the minimum of the observations.
    
    Returns:
    
    A double representing the minimum
  - getMax
```
public final double getMax()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the maximum of the observations.
    
    Returns:
    
    A double representing the maximum
  - getLastValue
```
public final double getLastValue()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the last observed data point
    
    Returns:
    
    A double representing the last observations
  - getKurtosis
```
public final double getKurtosis()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the kurtosis of the data
    
    Returns:
    
    A double representing the kurtosis
  - getSkewness
```
public final double getSkewness()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the skewness of the data
    
    Returns:
    
    A double representing the skewness
  - getStandardError
```
public final double getStandardError()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the standard error of the observations. Simply the generate standard deviation divided by the square root of the number of observations
    
    Returns:
    
    A double representing the standard error or Double.NaN if < 1 observation
  - getLag1Correlation
```
public final double getLag1Correlation()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the lag-1 generate correlation of the unweighted observations. Note: See Box, Jenkins, Reinsel, Time Series Analysis, 3rd edition, Prentice-Hall, pg 31
    
    Returns:
    
    A double representing the generate correlation or Double.NaN if <=2 observations
  - getLag1Covariance
```
public final double getLag1Covariance()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the lag-1 generate covariance of the unweighted observations. Note: See Box, Jenkins, Reinsel, Time Series Analysis, 3rd edition, Prentice-Hall, pg 31
    
    Returns:
    
    A double representing the generate covariance or Double.NaN if <=2 observations
  - getVonNeumannLag1TestStatistic
```
public final double getVonNeumannLag1TestStatistic()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the Von Neumann Lag 1 test statistic for checking the hypothesis that the data are uncorrelated Note: See Handbook of Simulation, Jerry Banks editor, McGraw-Hill, pg 253.
    
    Returns:
    
    A double representing the Von Neumann test statistic
  - getVonNeumannLag1TestStatisticPValue
```
public final double getVonNeumannLag1TestStatisticPValue()
```
    Description copied from interface: StatisticAccessorIfc
    
    Returns the asymptotic p-value for the Von Nueumann Lag-1 Test Statistic:
    Normal.stdNormalComplementaryCDF(getVonNeumannLag1TestStatistic());
    
    Returns:
    
    the p-value
  - getLeadingDigitRule
```
public final int getLeadingDigitRule(double a)
```
    Description copied from interface: StatisticAccessorIfc
    
    Computes the right most meaningful digit according to (int)Math.floor(Math.log10(a*getStandardError())) See doi 10.1287.opre.1080.0529 by Song and Schmeiser
    
    Parameters:
    
    a - the std error multiplier
    
    Returns:
    
    the meaningful digit
  - getBatchMeansIterator
```
public final java.util.Iterator<Statistic> getBatchMeansIterator()
```
    Returns an iterator across all the batch means collected so far
    
    Returns:
    
    an iterator across all the batch means collected so far
  - getSTSStandardError
```
public final double getSTSStandardError()
```
    Gets the standard error for the STS confidence interval
    
    Returns:
    
    standard error for the STS confidence interval
  - getSTSHalfWidth
```
public final double getSTSHalfWidth()
```
    Computes the half-width of a STS based confidence interval based on a 95% confidence level
    
    Returns:
    
    the half-width of a STS based confidence interval based on a 95% confidence level
  - getSTSHalfWidth
```
public final double getSTSHalfWidth(double level)
```
    Computes the half-width of a STS based confidence interval based on the supplied confidence coefficient.
    
    Parameters:
    
    level - the confidence level
    
    Returns:
    
    the half-width
  - getSTSAreaConstant
```
public final double getSTSAreaConstant()
```
    Computes an estimate of the STS Area Constant
    
    Returns:
    
    an estimate of the STS Area Constant
  - getAcrossBatchStatistic
```
public final StatisticAccessorIfc getAcrossBatchStatistic()
```
    Gets a StatisticAccessIfc that represents the across batch statistics
    
    Returns:
    
    Returns the statistic.
  - getCurrentBatchStatistic
```
public final StatisticAccessorIfc getCurrentBatchStatistic()
```
    Gets a StatisticAccessIfc for the current batch that is being collected. This is a statistic on the data within the batch
    
    Returns:
    
    Returns the statistic.
  - getUnBatchedStatistic
```
public final StatisticAccessorIfc getUnBatchedStatistic()
```
    Gets a StatisticAccessorIfc that represents statistics that have been collected on each unbatched data point This is the same as using a Statistic on the data
    
    Returns:
    
    Returns the statistic.
  - toString
```
public final java.lang.String toString()
```
    Description copied from interface: StatisticAccessorIfc
    
    Returns a String representation of the Statistic
    
    Specified by:
    
    toString in interface StatisticAccessorIfc
    
    Overrides:
    
    toString in class java.lang.Object
    
    Returns:
    
    A String with basic summary statistics
  - setBatchSize
```
protected final void setBatchSize(int batchSize)
```
    Sets the number of batches, must be >=2
    
    Parameters:
    
    batchSize - The number of batches to set
  - main
```
public static void main(java.lang.String[] args)
```

Class StandardizedTimeSeriesStatistic

Field Summary

Fields inherited from class jsl.utilities.statistic.AbstractStatistic

Fields inherited from interface jsl.utilities.statistic.ArraySaverIfc

Constructor Summary

Method Summary

Methods inherited from class jsl.utilities.statistic.AbstractStatistic

Methods inherited from class jsl.utilities.statistic.AbstractCollector

Methods inherited from class java.lang.Object

Methods inherited from interface jsl.utilities.statistic.CollectorIfc

Methods inherited from interface jsl.utilities.statistic.StatisticAccessorIfc

Field Detail

BATCH_SIZE

Constructor Detail

StandardizedTimeSeriesStatistic

StandardizedTimeSeriesStatistic

StandardizedTimeSeriesStatistic

StandardizedTimeSeriesStatistic

StandardizedTimeSeriesStatistic

StandardizedTimeSeriesStatistic

StandardizedTimeSeriesStatistic

StandardizedTimeSeriesStatistic

StandardizedTimeSeriesStatistic

StandardizedTimeSeriesStatistic

StandardizedTimeSeriesStatistic

StandardizedTimeSeriesStatistic

StandardizedTimeSeriesStatistic

Method Detail

getNumBatches

collect

reset

getCount

getAverage

getSum

getDeviationSumOfSquares

getVariance

getStandardDeviation

getHalfWidth

getMin

getMax

getLastValue

getKurtosis

getSkewness

getStandardError

getLag1Correlation

getLag1Covariance

getVonNeumannLag1TestStatistic

getVonNeumannLag1TestStatisticPValue

getLeadingDigitRule

getBatchMeansIterator

getSTSStandardError

getSTSHalfWidth

getSTSHalfWidth

getSTSAreaConstant

getAcrossBatchStatistic

getCurrentBatchStatistic

getUnBatchedStatistic

toString

setBatchSize

main