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

All Implemented Interfaces:

java.lang.Comparable<AbstractStatistic>, GetNameIfc, IdentityIfc, ArraySaverIfc, CollectorIfc, GetCSVStatisticIfc, StatisticAccessorIfc
```
public class AntitheticStatistic
extends AbstractStatistic
```
In progress...

Field Summary
- 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

AntitheticStatistic()

AntitheticStatistic(java.lang.String name)

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`java.lang.String`	`asString()`
`boolean`	`checkMean(double mean)`
`void`	`collect(double x)`	Collect on the supplied value
`long`	`estimateSampleSize(double desiredHW)`
`double`	`getAverage()`	Gets the unweighted average of the observations.
`double`	`getCount()`	Gets the count of the number of the observations.
`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()`	Gets the confidence interval half-width.
`double`	`getHalfWidth(double level)`	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`	`getObsWeightedSum()`
`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`	`getSum()`	Gets the sum of the observations.
`java.lang.String`	`getSummaryStatistics()`
`java.lang.String`	`getSummaryStatisticsHeader()`
`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:
`void`	`reset()`	Resets the collector as if no observations had been collected.

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, toString, 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, getName, getRelativeError, getRelativeWidth, getRelativeWidth, getStatistics, getStatisticsAsMap, toString

- Constructor Detail
  - AntitheticStatistic
```
public AntitheticStatistic()
```
  - AntitheticStatistic
```
public AntitheticStatistic(java.lang.String name)
```
    Parameters:
    
    name - the name of the statistic
- Method Detail
  - collect
```
public void collect(double x)
```
    Description copied from interface: CollectorIfc
    
    Collect on the supplied value
    
    Parameters:
    
    x - a double representing the observation
  - reset
```
public void reset()
```
    Description copied from interface: CollectorIfc
    
    Resets the collector as if no observations had been collected.
  - getCount
```
public double getCount()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the count of the number of the observations.
    
    Returns:
    
    A double representing the count
  - getSum
```
public double getSum()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the sum of the observations.
    
    Returns:
    
    A double representing the unweighted sum
  - getAverage
```
public 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.
  - getDeviationSumOfSquares
```
public 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 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 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.
  - getMin
```
public double getMin()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the minimum of the observations.
    
    Returns:
    
    A double representing the minimum
  - getMax
```
public double getMax()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the maximum of the observations.
    
    Returns:
    
    A double representing the maximum
  - getLastValue
```
public double getLastValue()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the last observed data point
    
    Returns:
    
    A double representing the last observations
  - getKurtosis
```
public double getKurtosis()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the kurtosis of the data
    
    Returns:
    
    A double representing the kurtosis
  - getSkewness
```
public double getSkewness()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the skewness of the data
    
    Returns:
    
    A double representing the skewness
  - getStandardError
```
public 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
  - getLag1Covariance
```
public 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
  - getLag1Correlation
```
public 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
  - getVonNeumannLag1TestStatistic
```
public 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 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 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
  - getHalfWidth
```
public double getHalfWidth()
```
    Description copied from interface: StatisticAccessorIfc
    
    Gets the confidence interval half-width. Simply the generate standard error times the confidence coefficient
    
    Returns:
    
    A double representing the half-width or Double.NaN if < 1 observation
  - getHalfWidth
```
public double getHalfWidth(double level)
```
    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:
    
    level - the confidence level
    
    Returns:
    
    A double representing the half-width or Double.NaN if < 1 observation
  - checkMean
```
public boolean checkMean(double mean)
```
  - getObsWeightedSum
```
public double getObsWeightedSum()
```
  - asString
```
public java.lang.String asString()
```
  - getSummaryStatistics
```
public java.lang.String getSummaryStatistics()
```
  - getSummaryStatisticsHeader
```
public java.lang.String getSummaryStatisticsHeader()
```
  - estimateSampleSize
```
public long estimateSampleSize(double desiredHW)
```

Constructor	Description
`AntitheticStatistic()`
`AntitheticStatistic(java.lang.String name)`

Class AntitheticStatistic

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

Constructor Detail

AntitheticStatistic

AntitheticStatistic

Method Detail

collect

reset

getCount

getSum

getAverage

getDeviationSumOfSquares

getVariance

getStandardDeviation

getMin

getMax

getLastValue

getKurtosis

getSkewness

getStandardError

getLag1Covariance

getLag1Correlation

getVonNeumannLag1TestStatistic

getVonNeumannLag1TestStatisticPValue

getLeadingDigitRule

getHalfWidth

getHalfWidth

checkMean

getObsWeightedSum

asString

getSummaryStatistics

getSummaryStatisticsHeader

estimateSampleSize