Class Mean
- All Implemented Interfaces:
Serializable
,DoubleConsumer
,AggregatableStatistic<Mean>
,StorelessUnivariateStatistic
,UnivariateStatistic
,WeightedEvaluation
,MathArrays.Function
mean = sum(x_i) / n
where n
is the number of observations.
When increment(double)
is used to add data incrementally from a
stream of (unstored) values, the value of the statistic that
getResult()
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 UnivariateStatistic.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 Double.NaN
if the dataset is empty. Note that
Double.NaN may also be returned if the input includes NaN and / or infinite
values.
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 the increment()
or
clear()
method, it must be synchronized externally.
- See Also:
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Field Summary
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Constructor Summary
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Method Summary
Modifier and TypeMethodDescriptionvoid
Aggregates the provided instance into this instance.void
clear()
Clears the internal state of the Statisticcopy()
Returns a copy of the statistic with the same internal state.double
evaluate
(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.NaN
if the designated subarray is empty.double
evaluate
(double[] values, int begin, int length) Returns the arithmetic mean of the entries in the specified portion of the input array, orDouble.NaN
if the designated subarray is empty.long
getN()
Returns the number of values that have been added.double
Returns the current value of the Statistic.void
increment
(double d) Updates the internal state of the statistic to reflect the addition of the new value.Methods inherited from class org.hipparchus.stat.descriptive.AbstractStorelessUnivariateStatistic
equals, hashCode, toString
Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
Methods inherited from interface org.hipparchus.stat.descriptive.AggregatableStatistic
aggregate, aggregate
Methods inherited from interface java.util.function.DoubleConsumer
andThen
Methods inherited from interface org.hipparchus.stat.descriptive.StorelessUnivariateStatistic
accept, incrementAll, incrementAll
Methods inherited from interface org.hipparchus.stat.descriptive.UnivariateStatistic
evaluate
Methods inherited from interface org.hipparchus.stat.descriptive.WeightedEvaluation
evaluate
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Field Details
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moment
protected final org.hipparchus.stat.descriptive.moment.FirstMoment momentFirst moment on which this statistic is based. -
incMoment
protected final boolean incMomentDetermines 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 Details
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Mean
public Mean()Constructs a Mean. -
Mean
public Mean(org.hipparchus.stat.descriptive.moment.FirstMoment m1) Constructs a Mean with an External Moment.- Parameters:
m1
- the moment
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Mean
Copy constructor, creates a newMean
identical to theoriginal
.- Parameters:
original
- theMean
instance to copy- Throws:
NullArgumentException
- if original is null
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Method Details
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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:
increment
in interfaceStorelessUnivariateStatistic
- Specified by:
increment
in classAbstractStorelessUnivariateStatistic
- Parameters:
d
- the new value.
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clear
public void clear()Clears the internal state of the Statistic- Specified by:
clear
in interfaceStorelessUnivariateStatistic
- Specified by:
clear
in classAbstractStorelessUnivariateStatistic
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getResult
public double getResult()Returns the current value of the Statistic.- Specified by:
getResult
in interfaceStorelessUnivariateStatistic
- Specified by:
getResult
in classAbstractStorelessUnivariateStatistic
- Returns:
- value of the statistic,
Double.NaN
if 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:
getN
in interfaceStorelessUnivariateStatistic
- Returns:
- the number of values.
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aggregate
Aggregates the provided instance into this instance.This method can be used to combine statistics computed over partitions or subsamples - i.e., the value of this instance after this operation should be the same as if a single statistic would have been applied over the combined dataset.
- Specified by:
aggregate
in interfaceAggregatableStatistic<Mean>
- Parameters:
other
- the instance to aggregate into this instance
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evaluate
Returns the arithmetic mean of the entries in the specified portion of the input array, orDouble.NaN
if the designated subarray is empty.- Specified by:
evaluate
in interfaceMathArrays.Function
- Specified by:
evaluate
in interfaceStorelessUnivariateStatistic
- Specified by:
evaluate
in interfaceUnivariateStatistic
- 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:
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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.NaN
if the designated subarray is empty.Throws
IllegalArgumentException
if either array is null.See
Mean
for 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
IllegalArgumentException
if 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:
evaluate
in 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
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copy
Returns a copy of the statistic with the same internal state.- Specified by:
copy
in interfaceStorelessUnivariateStatistic
- Specified by:
copy
in interfaceUnivariateStatistic
- Specified by:
copy
in classAbstractStorelessUnivariateStatistic
- Returns:
- a copy of the statistic
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