StatsAccumulator (Guava: Google Core Libraries for Java 20.0 API)

java.lang.Object
- com.google.common.math.StatsAccumulator

```
@Beta
 @GwtIncompatible
public final class StatsAccumulator
extends Object
```
A mutable object which accumulates double values and tracks some basic statistics over all the values added so far. The values may be added singly or in groups. This class is not thread safe.

Since:

20.0

Author:

Pete Gillin, Kevin Bourrillion

Constructor Summary

Constructors
Constructor and Description

StatsAccumulator()

Constructors
Constructor and Description
`StatsAccumulator()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`add(double value)` Adds the given value to the dataset.
`void`	`addAll(double... values)` Adds the given values to the dataset.
`void`	`addAll(int... values)` Adds the given values to the dataset.
`void`	`addAll(Iterable<? extends Number> values)` Adds the given values to the dataset.
`void`	`addAll(Iterator<? extends Number> values)` Adds the given values to the dataset.
`void`	`addAll(long... values)` Adds the given values to the dataset.
`void`	`addAll(Stats values)` Adds the given statistics to the dataset, as if the individual values used to compute the statistics had been added directly.
`long`	`count()` Returns the number of values.
`double`	`max()` Returns the highest value in the dataset.
`double`	`mean()` Returns the arithmetic mean of the values.
`double`	`min()` Returns the lowest value in the dataset.
`double`	`populationStandardDeviation()` Returns the population standard deviation of the values.
`double`	`populationVariance()` Returns the population variance of the values.
`double`	`sampleStandardDeviation()` Returns the corrected sample standard deviation of the values.
`double`	`sampleVariance()` Returns the unbaised sample variance of the values.
`Stats`	`snapshot()` Returns an immutable snapshot of the current statistics.
`double`	`sum()` Returns the sum of the values.

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

- Constructor Detail
  - StatsAccumulator
```
public StatsAccumulator()
```
- Method Detail
  - add
```
public void add(double value)
```
    Adds the given value to the dataset.
  - addAll
```
public void addAll(Iterable<? extends Number> values)
```
    Adds the given values to the dataset.
    
    Parameters:
    
    values - a series of values, which will be converted to double values (this may cause loss of precision)
  - addAll
```
public void addAll(Iterator<? extends Number> values)
```
    Adds the given values to the dataset.
    
    Parameters:
    
    values - a series of values, which will be converted to double values (this may cause loss of precision)
  - addAll
```
public void addAll(double... values)
```
    Adds the given values to the dataset.
    
    Parameters:
    
    values - a series of values
  - addAll
```
public void addAll(int... values)
```
    Adds the given values to the dataset.
    
    Parameters:
    
    values - a series of values
  - addAll
```
public void addAll(long... values)
```
    Adds the given values to the dataset.
    
    Parameters:
    
    values - a series of values, which will be converted to double values (this may cause loss of precision for longs of magnitude over 2^53 (slightly over 9e15))
  - addAll
```
public void addAll(Stats values)
```
    Adds the given statistics to the dataset, as if the individual values used to compute the statistics had been added directly.
  - snapshot
```
public Stats snapshot()
```
    Returns an immutable snapshot of the current statistics.
  - count
```
public long count()
```
    Returns the number of values.
  - mean
```
public double mean()
```
    Returns the arithmetic mean of the values. The count must be non-zero.
    If these values are a sample drawn from a population, this is also an unbiased estimator of the arithmetic mean of the population.
    Non-finite values
    
    If the dataset contains Double.NaN then the result is Double.NaN. If it contains both Double.POSITIVE_INFINITY and Double.NEGATIVE_INFINITY then the result is Double.NaN. If it contains Double.POSITIVE_INFINITY and finite values only or Double.POSITIVE_INFINITY only, the result is Double.POSITIVE_INFINITY. If it contains Double.NEGATIVE_INFINITY and finite values only or Double.NEGATIVE_INFINITY only, the result is Double.NEGATIVE_INFINITY.
    
    Throws:
    
    IllegalStateException - if the dataset is empty
  - sum
```
public final double sum()
```
    Returns the sum of the values.
    Non-finite values
    
    If the dataset contains Double.NaN then the result is Double.NaN. If it contains both Double.POSITIVE_INFINITY and Double.NEGATIVE_INFINITY then the result is Double.NaN. If it contains Double.POSITIVE_INFINITY and finite values only or Double.POSITIVE_INFINITY only, the result is Double.POSITIVE_INFINITY. If it contains Double.NEGATIVE_INFINITY and finite values only or Double.NEGATIVE_INFINITY only, the result is Double.NEGATIVE_INFINITY.
  - populationVariance
```
public final double populationVariance()
```
    Returns the population variance of the values. The count must be non-zero.
    This is guaranteed to return zero if the dataset contains only exactly one finite value. It is not guaranteed to return zero when the dataset consists of the same value multiple times, due to numerical errors. However, it is guaranteed never to return a negative result.
    Non-finite values
    
    If the dataset contains any non-finite values (Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY, or Double.NaN) then the result is Double.NaN.
    
    Throws:
    
    IllegalStateException - if the dataset is empty
  - populationStandardDeviation
```
public final double populationStandardDeviation()
```
    Returns the population standard deviation of the values. The count must be non-zero.
    This is guaranteed to return zero if the dataset contains only exactly one finite value. It is not guaranteed to return zero when the dataset consists of the same value multiple times, due to numerical errors. However, it is guaranteed never to return a negative result.
    Non-finite values
    
    If the dataset contains any non-finite values (Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY, or Double.NaN) then the result is Double.NaN.
    
    Throws:
    
    IllegalStateException - if the dataset is empty
  - sampleVariance
```
public final double sampleVariance()
```
    Returns the unbaised sample variance of the values. If this dataset is a sample drawn from a population, this is an unbiased estimator of the population variance of the population. The count must be greater than one.
    This is not guaranteed to return zero when the dataset consists of the same value multiple times, due to numerical errors. However, it is guaranteed never to return a negative result.
    Non-finite values
    
    If the dataset contains any non-finite values (Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY, or Double.NaN) then the result is Double.NaN.
    
    Throws:
    
    IllegalStateException - if the dataset is empty or contains a single value
  - sampleStandardDeviation
```
public final double sampleStandardDeviation()
```
    Returns the corrected sample standard deviation of the values. If this dataset is a sample drawn from a population, this is an estimator of the population standard deviation of the population which is less biased than populationStandardDeviation() (the unbiased estimator depends on the distribution). The count must be greater than one.
    This is not guaranteed to return zero when the dataset consists of the same value multiple times, due to numerical errors. However, it is guaranteed never to return a negative result.
    Non-finite values
    
    If the dataset contains any non-finite values (Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY, or Double.NaN) then the result is Double.NaN.
    
    Throws:
    
    IllegalStateException - if the dataset is empty or contains a single value
  - min
```
public double min()
```
    Returns the lowest value in the dataset. The count must be non-zero.
    Non-finite values
    
    If the dataset contains Double.NaN then the result is Double.NaN. If it contains Double.NEGATIVE_INFINITY and not Double.NaN then the result is Double.NEGATIVE_INFINITY. If it contains Double.POSITIVE_INFINITY and finite values only then the result is the lowest finite value. If it contains Double.POSITIVE_INFINITY only then the result is Double.POSITIVE_INFINITY.
    
    Throws:
    
    IllegalStateException - if the dataset is empty
  - max
```
public double max()
```
    Returns the highest value in the dataset. The count must be non-zero.
    Non-finite values
    
    If the dataset contains Double.NaN then the result is Double.NaN. If it contains Double.POSITIVE_INFINITY and not Double.NaN then the result is Double.POSITIVE_INFINITY. If it contains Double.NEGATIVE_INFINITY and finite values only then the result is the highest finite value. If it contains Double.NEGATIVE_INFINITY only then the result is Double.NEGATIVE_INFINITY.
    
    Throws:
    
    IllegalStateException - if the dataset is empty

Class StatsAccumulator

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

StatsAccumulator

Method Detail

add

addAll

addAll

addAll

addAll

addAll

addAll

snapshot

count

mean

Non-finite values

sum

Non-finite values

populationVariance

Non-finite values

populationStandardDeviation

Non-finite values

sampleVariance

Non-finite values

sampleStandardDeviation

Non-finite values

min

Non-finite values

max

Non-finite values