Guava: Google Core Libraries for Java 33.1.0-jre · com.google.common.math.Stats

Modifier and Type	Field and Description
pack-priv static final int	BYTES The size of byte array representation in bytes.
private final long	count
private final double	max
private final double	mean
private final double	min
private static final long	serialVersionUID
private final double	sumOfSquaresOfDeltas

Access	Constructor and Description
pack-priv	Stats(long count, double mean, double sumOfSquaresOfDeltas, double min, double max) Internal constructor.

Method Summary

Modifier and Type	Method and Description
public long	count() Returns the number of values.
public boolean	equals(Object the reference object with which to compare. obj) Overrides java.lang.Object.equals. Indicates whether some other object is "equal to" this one.
public static Stats	fromByteArray(byte[] byteArray) Creates a Stats instance from the given byte representation which was obtained by `toByteArray`.
public int	hashCode() Overrides java.lang.Object.hashCode. Returns a hash code value for this object.
public double	max() Returns the highest value in the dataset.
public double	mean() Returns the arithmetic mean of the values.
public static double	meanOf(Iterable<? extends Number> a series of values, which will be converted to `double` values (this may cause loss of precision) values) Returns the arithmetic mean of the values.
public static double	meanOf(Iterator<? extends Number> a series of values, which will be converted to `double` values (this may cause loss of precision) values) Returns the arithmetic mean of the values.
public static double	meanOf(double... a series of values values) Returns the arithmetic mean of the values.
public static double	meanOf(int... a series of values values) Returns the arithmetic mean of the values.
public static double	meanOf(long... 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)) values) Returns the arithmetic mean of the values.
public double	min() Returns the lowest value in the dataset.
public static Stats	of(Iterable<? extends Number> a series of values, which will be converted to `double` values (this may cause loss of precision) values) Returns statistics over a dataset containing the given values.
public static Stats	of(Iterator<? extends Number> a series of values, which will be converted to `double` values (this may cause loss of precision) values) Returns statistics over a dataset containing the given values.
public static Stats	of(double... a series of values values) Returns statistics over a dataset containing the given values.
public static Stats	of(int... a series of values values) Returns statistics over a dataset containing the given values.
public static Stats	of(long... 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)) values) Returns statistics over a dataset containing the given values.
public static Stats	of(DoubleStream a series of values values) Returns statistics over a dataset containing the given values.
public static Stats	of(IntStream a series of values values) Returns statistics over a dataset containing the given values.
public static Stats	of(LongStream 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)) values) Returns statistics over a dataset containing the given values.
public double	populationStandardDeviation() Returns the population standard deviation of the values.
public double	populationVariance() Returns the population variance of the values.
pack-priv static Stats	readFrom(ByteBuffer A `ByteBuffer` with at least BYTES `ByteBuffer#remaining`, ordered as `ByteOrder#LITTLE_ENDIAN`, from which a BYTES-long byte representation of this instance is read. In the process increases the position of `ByteBuffer` by BYTES. buffer) Creates a Stats instance from the byte representation read from the given `ByteBuffer`.
public double	sampleStandardDeviation() Returns the corrected sample standard deviation of the values.
public double	sampleVariance() Returns the unbiased sample variance of the values.
public double	sum() Returns the sum of the values.
pack-priv double	sumOfSquaresOfDeltas()
public byte[]	toByteArray() Gets a byte array representation of this instance.
public static Collector<Number, StatsAccumulator, Stats>	toStats() Returns a `Collector` which accumulates statistics from a `java.util.stream.Stream` of any type of boxed `Number` into a `Stats`.
public String	toString() Overrides java.lang.Object.toString. Returns a string representation of the object.
pack-priv void	writeTo(ByteBuffer A `ByteBuffer` with at least BYTES `ByteBuffer#remaining`, ordered as `ByteOrder#LITTLE_ENDIAN`, to which a BYTES-long byte representation of this instance is written. In the process increases the position of `ByteBuffer` by BYTES. buffer) Writes to the given `ByteBuffer` a byte representation of this instance.

Inherited from java.lang.Object:: clone finalize getClass notify notifyAll wait wait wait

BYTES	back to summary
pack-priv static final int BYTES The size of byte array representation in bytes.

count	back to summary
private final long count

max	back to summary
private final double max

mean	back to summary
private final double mean

min	back to summary
private final double min

serialVersionUID	back to summary
private static final long serialVersionUID

sumOfSquaresOfDeltas	back to summary
private final double sumOfSquaresOfDeltas

Stats	back to summary
pack-priv Stats(long count, double mean, double sumOfSquaresOfDeltas, double min, double max) Internal constructor. Users should use `of` or `StatsAccumulator#snapshot`. To ensure that the created instance obeys its contract, the parameters should satisfy the following constraints. This is the callers responsibility and is not enforced here. If `count` is 0, `mean` may have any finite value (its only usage will be to get multiplied by 0 to calculate the sum), and the other parameters may have any values (they will not be used). If `count` is 1, `sumOfSquaresOfDeltas` must be exactly 0.0 or `Double#NaN`.

Method Detail

count	back to summary
public long count() Returns the number of values.

equals back to summary

equals	back to summary
public boolean equals(Object obj) Overrides java.lang.Object.equals. Doc from java.lang.Object.equals. Indicates whether some other object is "equal to" this one. The `equals` method implements an equivalence relation on non-null object references: It is reflexive: for any non-null reference value `x`, `x.equals(x)` should return `true`. It is symmetric: for any non-null reference values `x` and `y`, `x.equals(y)` should return `true` if and only if `y.equals(x)` returns `true`. It is transitive: for any non-null reference values `x`, `y`, and `z`, if `x.equals(y)` returns `true` and `y.equals(z)` returns `true`, then `x.equals(z)` should return `true`. It is consistent: for any non-null reference values `x` and `y`, multiple invocations of `x.equals(y)` consistently return `true` or consistently return `false`, provided no information used in `equals` comparisons on the objects is modified. For any non-null reference value `x`, `x.equals(null)` should return `false`. An equivalence relation partitions the elements it operates on into equivalence classes; all the members of an equivalence class are equal to each other. Members of an equivalence class are substitutable for each other, at least for some purposes. Note This tests exact equality of the calculated statistics, including the floating point values. Two instances are guaranteed to be considered equal if one is copied from the other using `second = new StatsAccumulator().addAll(first).snapshot()`, if both were obtained by calling `snapshot()` on the same `StatsAccumulator` without adding any values in between the two calls, or if one is obtained from the other after round-tripping through java serialization. However, floating point rounding errors mean that it may be false for some instances where the statistics are mathematically equal, including instances constructed from the same values in a different order... or (in the general case) even in the same order. (It is guaranteed to return true for instances constructed from the same values in the same order if `strictfp` is in effect, or if the system architecture guarantees `strictfp`-like semantics.) Parameters obj:Object the reference object with which to compare. Returns:boolean `true` if this object is the same as the obj argument; `false` otherwise. Annotations @Override

public boolean equals(Object obj)

Overrides java.lang.Object.equals.

Doc from java.lang.Object.equals.

Indicates whether some other object is "equal to" this one.

The equals method implements an equivalence relation on non-null object references:

It is reflexive: for any non-null reference value x, x.equals(x) should return true.
It is symmetric: for any non-null reference values x and y, x.equals(y) should return true if and only if y.equals(x) returns true.
It is transitive: for any non-null reference values x, y, and z, if x.equals(y) returns true and y.equals(z) returns true, then x.equals(z) should return true.
It is consistent: for any non-null reference values x and y, multiple invocations of x.equals(y) consistently return true or consistently return false, provided no information used in equals comparisons on the objects is modified.
For any non-null reference value x, x.equals(null) should return false.

An equivalence relation partitions the elements it operates on into equivalence classes; all the members of an equivalence class are equal to each other. Members of an equivalence class are substitutable for each other, at least for some purposes.

Note

This tests exact equality of the calculated statistics, including the floating point values. Two instances are guaranteed to be considered equal if one is copied from the other using second = new StatsAccumulator().addAll(first).snapshot(), if both were obtained by calling snapshot() on the same StatsAccumulator without adding any values in between the two calls, or if one is obtained from the other after round-tripping through java serialization. However, floating point rounding errors mean that it may be false for some instances where the statistics are mathematically equal, including instances constructed from the same values in a different order... or (in the general case) even in the same order. (It is guaranteed to return true for instances constructed from the same values in the same order if strictfp is in effect, or if the system architecture guarantees strictfp-like semantics.)

Parameters

obj:Object: the reference object with which to compare.

Returns:boolean

true if this object is the same as the obj argument; false otherwise.

Annotations

@Override

fromByteArray	back to summary
public static Stats fromByteArray(byte[] byteArray) Creates a Stats instance from the given byte representation which was obtained by `toByteArray`. Note No guarantees are made regarding stability of the representation between versions.

hashCode back to summary

hashCode	back to summary
public int hashCode() Overrides java.lang.Object.hashCode. Doc from java.lang.Object.hashCode. Returns a hash code value for this object. This method is supported for the benefit of hash tables such as those provided by `java.util.HashMap`. The general contract of `hashCode` is: Whenever it is invoked on the same object more than once during an execution of a Java application, the `hashCode` method must consistently return the same integer, provided no information used in `equals` comparisons on the object is modified. This integer need not remain consistent from one execution of an application to another execution of the same application. If two objects are equal according to the `equals` method, then calling the `hashCode` method on each of the two objects must produce the same integer result. It is not required that if two objects are unequal according to the `equals` method, then calling the `hashCode` method on each of the two objects must produce distinct integer results. However, the programmer should be aware that producing distinct integer results for unequal objects may improve the performance of hash tables. Note This hash code is consistent with exact equality of the calculated statistics, including the floating point values. See the note on `equals` for details. Returns:int a hash code value for this object Annotations @Override

public int hashCode()

Overrides java.lang.Object.hashCode.

Doc from java.lang.Object.hashCode.

Returns a hash code value for this object. This method is supported for the benefit of hash tables such as those provided by java.util.HashMap.

The general contract of hashCode is:

Whenever it is invoked on the same object more than once during an execution of a Java application, the hashCode method must consistently return the same integer, provided no information used in equals comparisons on the object is modified. This integer need not remain consistent from one execution of an application to another execution of the same application.
If two objects are equal according to the equals method, then calling the hashCode method on each of the two objects must produce the same integer result.
It is not required that if two objects are unequal according to the equals method, then calling the hashCode method on each of the two objects must produce distinct integer results. However, the programmer should be aware that producing distinct integer results for unequal objects may improve the performance of hash tables.

Note

This hash code is consistent with exact equality of the calculated statistics, including the floating point values. See the note on equals for details.

Returns:int

a hash code value for this object

Annotations

@Override

max back to summary

max	back to summary
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`. Exceptions IllegalStateException: if the dataset is empty

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.

Exceptions

IllegalStateException:: if the dataset is empty

mean back to summary

mean	back to summary
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`. If you only want to calculate the mean, use `meanOf` instead of creating a `Stats` instance. Exceptions IllegalStateException: if the dataset is empty

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.

If you only want to calculate the mean, use meanOf instead of creating a Stats instance.

Exceptions

IllegalStateException:: if the dataset is empty

meanOf back to summary

meanOf	back to summary
public static double meanOf(Iterable<? extends Number> values) Returns the arithmetic mean of the values. The count must be non-zero. The definition of the mean is the same as `Stats#mean`. Parameters values:Iterable<? extends Number> a series of values, which will be converted to `double` values (this may cause loss of precision) Exceptions IllegalArgumentException: if the dataset is empty

public static double meanOf(Iterable<? extends Number> values)

Returns the arithmetic mean of the values. The count must be non-zero.

The definition of the mean is the same as Stats#mean.

Parameters

values:Iterable<? extends Number>: a series of values, which will be converted to double values (this may cause loss of precision)

Exceptions

IllegalArgumentException:: if the dataset is empty

meanOf back to summary

meanOf	back to summary
public static double meanOf(Iterator<? extends Number> values) Returns the arithmetic mean of the values. The count must be non-zero. The definition of the mean is the same as `Stats#mean`. Parameters values:Iterator<? extends Number> a series of values, which will be converted to `double` values (this may cause loss of precision) Exceptions IllegalArgumentException: if the dataset is empty

public static double meanOf(Iterator<? extends Number> values)

Returns the arithmetic mean of the values. The count must be non-zero.

The definition of the mean is the same as Stats#mean.

Parameters

values:Iterator<? extends Number>: a series of values, which will be converted to double values (this may cause loss of precision)

Exceptions

IllegalArgumentException:: if the dataset is empty

meanOf back to summary

meanOf	back to summary
public static double meanOf(double... values) Returns the arithmetic mean of the values. The count must be non-zero. The definition of the mean is the same as `Stats#mean`. Parameters values:double[] a series of values Exceptions IllegalArgumentException: if the dataset is empty

public static double meanOf(double... values)

Returns the arithmetic mean of the values. The count must be non-zero.

The definition of the mean is the same as Stats#mean.

Parameters

values:double[]: a series of values

Exceptions

IllegalArgumentException:: if the dataset is empty

meanOf back to summary

meanOf	back to summary
public static double meanOf(int... values) Returns the arithmetic mean of the values. The count must be non-zero. The definition of the mean is the same as `Stats#mean`. Parameters values:int[] a series of values Exceptions IllegalArgumentException: if the dataset is empty

public static double meanOf(int... values)

Returns the arithmetic mean of the values. The count must be non-zero.

The definition of the mean is the same as Stats#mean.

Parameters

values:int[]: a series of values

Exceptions

IllegalArgumentException:: if the dataset is empty

meanOf back to summary

meanOf	back to summary
public static double meanOf(long... values) Returns the arithmetic mean of the values. The count must be non-zero. The definition of the mean is the same as `Stats#mean`. Parameters values:long[] 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)) Exceptions IllegalArgumentException: if the dataset is empty

public static double meanOf(long... values)

Returns the arithmetic mean of the values. The count must be non-zero.

The definition of the mean is the same as Stats#mean.

Parameters

values:long[]: 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))

Exceptions

IllegalArgumentException:: if the dataset is empty

min back to summary

min	back to summary
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`. Exceptions IllegalStateException: if the dataset is empty

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.

Exceptions

IllegalStateException:: if the dataset is empty

of back to summary

of	back to summary
public static Stats of(Iterable<? extends Number> values) Returns statistics over a dataset containing the given values. Parameters values:Iterable<? extends Number> a series of values, which will be converted to `double` values (this may cause loss of precision)

public static Stats of(Iterable<? extends Number> values)

Returns statistics over a dataset containing the given values.

Parameters

values:Iterable<? extends Number>: a series of values, which will be converted to double values (this may cause loss of precision)

of back to summary

of	back to summary
public static Stats of(Iterator<? extends Number> values) Returns statistics over a dataset containing the given values. The iterator will be completely consumed by this method. Parameters values:Iterator<? extends Number> a series of values, which will be converted to `double` values (this may cause loss of precision)

public static Stats of(Iterator<? extends Number> values)

Returns statistics over a dataset containing the given values. The iterator will be completely consumed by this method.

Parameters

values:Iterator<? extends Number>: a series of values, which will be converted to double values (this may cause loss of precision)

of	back to summary
public static Stats of(double... values) Returns statistics over a dataset containing the given values. Parameters values:double[] a series of values

back to summary

public static Stats of(double... values)

Returns statistics over a dataset containing the given values.

Parameters

values:double[]: a series of values

of	back to summary
public static Stats of(int... values) Returns statistics over a dataset containing the given values. Parameters values:int[] a series of values

back to summary

public static Stats of(int... values)

Returns statistics over a dataset containing the given values.

Parameters

values:int[]: a series of values

of back to summary

of	back to summary
public static Stats of(long... values) Returns statistics over a dataset containing the given values. Parameters values:long[] 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))

public static Stats of(long... values)

Returns statistics over a dataset containing the given values.

Parameters

values:long[]: 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))

of back to summary

of	back to summary
public static Stats of(DoubleStream values) Returns statistics over a dataset containing the given values. The stream will be completely consumed by this method. If you have a `Stream<Double>` rather than a `DoubleStream`, you should collect the values using `toStats()` instead. Parameters values:DoubleStream a series of values Since 28.2

public static Stats of(DoubleStream values)

Returns statistics over a dataset containing the given values. The stream will be completely consumed by this method.

If you have a Stream<Double> rather than a DoubleStream, you should collect the values using toStats() instead.

Parameters

values:DoubleStream: a series of values

Since

28.2

of back to summary

of	back to summary
public static Stats of(IntStream values) Returns statistics over a dataset containing the given values. The stream will be completely consumed by this method. If you have a `Stream<Integer>` rather than an `IntStream`, you should collect the values using `toStats()` instead. Parameters values:IntStream a series of values Since 28.2

public static Stats of(IntStream values)

Returns statistics over a dataset containing the given values. The stream will be completely consumed by this method.

If you have a Stream<Integer> rather than an IntStream, you should collect the values using toStats() instead.

Parameters

values:IntStream: a series of values

Since

28.2

of back to summary

of	back to summary
public static Stats of(LongStream values) Returns statistics over a dataset containing the given values. The stream will be completely consumed by this method. If you have a `Stream<Long>` rather than a `LongStream`, you should collect the values using `toStats()` instead. Parameters values:LongStream 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)) Since 28.2

public static Stats of(LongStream values)

Returns statistics over a dataset containing the given values. The stream will be completely consumed by this method.

If you have a Stream<Long> rather than a LongStream, you should collect the values using toStats() instead.

Parameters

values:LongStream: 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))

Since

28.2

populationStandardDeviation back to summary

populationStandardDeviation	back to summary
public 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`. Exceptions IllegalStateException: if the dataset is empty

public 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.

Exceptions

IllegalStateException:: if the dataset is empty

populationVariance back to summary

populationVariance	back to summary
public 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`. Exceptions IllegalStateException: if the dataset is empty

public double populationVariance()

Returns the population variance of the values. The count must be non-zero.

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.

Exceptions

IllegalStateException:: if the dataset is empty

readFrom back to summary

readFrom	back to summary
pack-priv static Stats readFrom(ByteBuffer buffer) Creates a Stats instance from the byte representation read from the given `ByteBuffer`. Note No guarantees are made regarding stability of the representation between versions. Parameters buffer:ByteBuffer A `ByteBuffer` with at least BYTES `ByteBuffer#remaining`, ordered as `ByteOrder#LITTLE_ENDIAN`, from which a BYTES-long byte representation of this instance is read. In the process increases the position of `ByteBuffer` by BYTES.

pack-priv static Stats readFrom(ByteBuffer buffer)

Creates a Stats instance from the byte representation read from the given ByteBuffer.

Note

No guarantees are made regarding stability of the representation between versions.

Parameters

buffer:ByteBuffer: A ByteBuffer with at least BYTES ByteBuffer#remaining, ordered as ByteOrder#LITTLE_ENDIAN, from which a BYTES-long byte representation of this instance is read. In the process increases the position of ByteBuffer by BYTES.

sampleStandardDeviation back to summary

sampleStandardDeviation	back to summary
public 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`. Exceptions IllegalStateException: if the dataset is empty or contains a single value

public 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.

Exceptions

IllegalStateException:: if the dataset is empty or contains a single value

sampleVariance back to summary

sampleVariance	back to summary
public double sampleVariance() Returns the unbiased 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`. Exceptions IllegalStateException: if the dataset is empty or contains a single value

public double sampleVariance()

Returns the unbiased 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.

Exceptions

IllegalStateException:: if the dataset is empty or contains a single value

sum back to summary

sum	back to summary
public 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`.

public double sum()

Returns the sum of the values.

Non-finite values

sumOfSquaresOfDeltas	back to summary
pack-priv double sumOfSquaresOfDeltas()

toByteArray	back to summary
public byte[] toByteArray() Gets a byte array representation of this instance. Note No guarantees are made regarding stability of the representation between versions.

toStats back to summary

toStats	back to summary
public static Collector<Number, StatsAccumulator, Stats> toStats() Returns a `Collector` which accumulates statistics from a `java.util.stream.Stream` of any type of boxed `Number` into a `Stats`. Use by calling `boxedNumericStream.collect(toStats())`. The numbers will be converted to `double` values (which may cause loss of precision). If you have any of the primitive streams `DoubleStream`, `IntStream`, or `LongStream`, you should use the factory method `of` instead. Since 28.2

public static Collector<Number, StatsAccumulator, Stats> toStats()

Returns a Collector which accumulates statistics from a java.util.stream.Stream of any type of boxed Number into a Stats. Use by calling boxedNumericStream.collect(toStats()). The numbers will be converted to double values (which may cause loss of precision).

If you have any of the primitive streams DoubleStream, IntStream, or LongStream, you should use the factory method of instead.

Since: 28.2

toString	back to summary
public String toString() Overrides java.lang.Object.toString. Doc from java.lang.Object.toString. Returns a string representation of the object. Returns:String a string representation of the object Annotations @Override

toString

back to summary

public String toString()

Overrides java.lang.Object.toString.

Doc from java.lang.Object.toString.

Returns a string representation of the object.

Returns:String

a string representation of the object

Annotations

@Override

writeTo back to summary

writeTo	back to summary
pack-priv void writeTo(ByteBuffer buffer) Writes to the given `ByteBuffer` a byte representation of this instance. Note No guarantees are made regarding stability of the representation between versions. Parameters buffer:ByteBuffer A `ByteBuffer` with at least BYTES `ByteBuffer#remaining`, ordered as `ByteOrder#LITTLE_ENDIAN`, to which a BYTES-long byte representation of this instance is written. In the process increases the position of `ByteBuffer` by BYTES.

pack-priv void writeTo(ByteBuffer buffer)

Writes to the given ByteBuffer a byte representation of this instance.

Note

No guarantees are made regarding stability of the representation between versions.

Parameters

buffer:ByteBuffer: A ByteBuffer with at least BYTES ByteBuffer#remaining, ordered as ByteOrder#LITTLE_ENDIAN, to which a BYTES-long byte representation of this instance is written. In the process increases the position of ByteBuffer by BYTES.

public final Class Stats

Field Summary

Constructor Summary

Method Summary

Field Detail

Constructor Detail

Method Detail

Non-finite values

Non-finite values

Non-finite values

Non-finite values

Non-finite values

Non-finite values

Non-finite values

Non-finite values