Class Mean
- java.lang.Object
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- org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic
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- org.apache.commons.math4.legacy.stat.descriptive.moment.Mean
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- All Implemented Interfaces:
MathArrays.Function,StorelessUnivariateStatistic,UnivariateStatistic,WeightedEvaluation
public class Mean extends AbstractStorelessUnivariateStatistic implements WeightedEvaluation
Computes the arithmetic mean of a set of values. Uses the definitional formula:mean = sum(x_i) / n
where
nis the number of observations.When
increment(double)is used to add data incrementally from a stream of (unstored) values, the value of the statistic thatgetResult()returns is computed using the following recursive updating algorithm:- Initialize
m =the first value - For each additional value, update using
m = m + (new value - m) / (number of observations)
If
AbstractStorelessUnivariateStatistic.evaluate(double[])is used to compute the mean of an array of stored values, a two-pass, corrected algorithm is used, starting with the definitional formula computed using the array of stored values and then correcting this by adding the mean deviation of the data values from the arithmetic mean. See, e.g. "Comparison of Several Algorithms for Computing Sample Means and Variances," Robert F. Ling, Journal of the American Statistical Association, Vol. 69, No. 348 (Dec., 1974), pp. 859-866.Returns
Note that this implementation is not synchronized. If multiple threads access an instance of this class concurrently, and at least one of the threads invokes theDouble.NaNif the dataset is empty. Note that Double.NaN may also be returned if the input includes NaN and / or infinite values.increment()orclear()method, it must be synchronized externally.
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description voidclear()Clears the internal state of the Statistic.Meancopy()Returns a copy of the statistic with the same internal state.static voidcopy(Mean source, Mean dest)Copies source to dest.doubleevaluate(double[] values, double[] weights)Returns the weighted arithmetic mean of the entries in the input array.doubleevaluate(double[] values, double[] weights, int begin, int length)Returns the weighted arithmetic mean of the entries in the specified portion of the input array, orDouble.NaNif the designated subarray is empty.doubleevaluate(double[] values, int begin, int length)Returns the arithmetic mean of the entries in the specified portion of the input array, orDouble.NaNif the designated subarray is empty.longgetN()Returns the number of values that have been added.doublegetResult()Returns the current value of the Statistic.voidincrement(double d)Updates the internal state of the statistic to reflect the addition of the new value.-
Methods inherited from class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic
equals, evaluate, hashCode, incrementAll, incrementAll
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Field Detail
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moment
protected org.apache.commons.math4.legacy.stat.descriptive.moment.FirstMoment moment
First moment on which this statistic is based.
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incMoment
protected boolean incMoment
Determines whether or not this statistic can be incremented or cleared.Statistics based on (constructed from) external moments cannot be incremented or cleared.
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Constructor Detail
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Mean
public Mean()
Constructs a Mean.
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Mean
public Mean(org.apache.commons.math4.legacy.stat.descriptive.moment.FirstMoment m1)
Constructs a Mean with an External Moment.- Parameters:
m1- the moment
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Mean
public Mean(Mean original) throws NullArgumentException
Copy constructor, creates a newMeanidentical to theoriginal.- Parameters:
original- theMeaninstance to copy- Throws:
NullArgumentException- if original is null
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Method Detail
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increment
public void increment(double d)
Updates the internal state of the statistic to reflect the addition of the new value.Note that when
Mean(FirstMoment)is used to create a Mean, this method does nothing. In that case, the FirstMoment should be incremented directly.- Specified by:
incrementin interfaceStorelessUnivariateStatistic- Specified by:
incrementin classAbstractStorelessUnivariateStatistic- Parameters:
d- the new value.
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clear
public void clear()
Clears the internal state of the Statistic.- Specified by:
clearin interfaceStorelessUnivariateStatistic- Specified by:
clearin classAbstractStorelessUnivariateStatistic
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getResult
public double getResult()
Returns the current value of the Statistic.- Specified by:
getResultin interfaceStorelessUnivariateStatistic- Specified by:
getResultin classAbstractStorelessUnivariateStatistic- Returns:
- value of the statistic,
Double.NaNif it has been cleared or just instantiated.
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getN
public long getN()
Returns the number of values that have been added.- Specified by:
getNin interfaceStorelessUnivariateStatistic- Returns:
- the number of values.
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evaluate
public double evaluate(double[] values, int begin, int length) throws MathIllegalArgumentException
Returns the arithmetic mean of the entries in the specified portion of the input array, orDouble.NaNif the designated subarray is empty.Throws
IllegalArgumentExceptionif the array is null.See
Meanfor details on the computing algorithm.- Specified by:
evaluatein interfaceMathArrays.Function- Specified by:
evaluatein interfaceUnivariateStatistic- Overrides:
evaluatein classAbstractStorelessUnivariateStatistic- Parameters:
values- the input arraybegin- index of the first array element to includelength- the number of elements to include- Returns:
- the mean of the values or Double.NaN if length = 0
- Throws:
MathIllegalArgumentException- if the array is null or the array index parameters are not valid- See Also:
UnivariateStatistic.evaluate(double[], int, int)
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evaluate
public double evaluate(double[] values, double[] weights, int begin, int length) throws MathIllegalArgumentException
Returns the weighted arithmetic mean of the entries in the specified portion of the input array, orDouble.NaNif the designated subarray is empty.Throws
IllegalArgumentExceptionif either array is null.See
Meanfor details on the computing algorithm. The two-pass algorithm described above is used here, with weights applied in computing both the original estimate and the correction factor.Throws
IllegalArgumentExceptionif any of the following are true:- the values array is null
- the weights array is null
- the weights array does not have the same length as the values array
- the weights array contains one or more infinite values
- the weights array contains one or more NaN values
- the weights array contains negative values
- the start and length arguments do not determine a valid array
- Specified by:
evaluatein interfaceWeightedEvaluation- Parameters:
values- the input arrayweights- the weights arraybegin- index of the first array element to includelength- the number of elements to include- Returns:
- the mean of the values or Double.NaN if length = 0
- Throws:
MathIllegalArgumentException- if the parameters are not valid- Since:
- 2.1
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evaluate
public double evaluate(double[] values, double[] weights) throws MathIllegalArgumentException
Returns the weighted arithmetic mean of the entries in the input array.Throws
MathIllegalArgumentExceptionif either array is null.See
Meanfor details on the computing algorithm. The two-pass algorithm described above is used here, with weights applied in computing both the original estimate and the correction factor.Throws
MathIllegalArgumentExceptionif any of the following are true:- the values array is null
- the weights array is null
- the weights array does not have the same length as the values array
- the weights array contains one or more infinite values
- the weights array contains one or more NaN values
- the weights array contains negative values
- Specified by:
evaluatein interfaceWeightedEvaluation- Parameters:
values- the input arrayweights- the weights array- Returns:
- the mean of the values or Double.NaN if length = 0
- Throws:
MathIllegalArgumentException- if the parameters are not valid- Since:
- 2.1
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copy
public Mean copy()
Returns a copy of the statistic with the same internal state.- Specified by:
copyin interfaceStorelessUnivariateStatistic- Specified by:
copyin interfaceUnivariateStatistic- Specified by:
copyin classAbstractStorelessUnivariateStatistic- Returns:
- a copy of the statistic
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copy
public static void copy(Mean source, Mean dest) throws NullArgumentException
Copies source to dest.Neither source nor dest can be null.
- Parameters:
source- Mean to copydest- Mean to copy to- Throws:
NullArgumentException- if either source or dest is null
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