Namespaces

Types in MathNet.Numerics.Statistics

Type SortedArrayStatistics

Namespace MathNet.Numerics.Statistics

Statistics operating on an array already sorted ascendingly.

Static Functions

Public Static Functions

double EmpiricalCDF(Double[] data, double x)

Estimates the empirical cumulative distribution function (CDF) at x from the sorted data array (ascending).
Parameters
Double[] data

The data sample sequence.

double x

The value where to estimate the CDF at.

double EmpiricalCDF(Single[] data, float x)

Estimates the empirical cumulative distribution function (CDF) at x from the sorted data array (ascending).
Parameters
Single[] data

The data sample sequence.

float x

The value where to estimate the CDF at.

Double[] FiveNumberSummary(Double[] data)

Estimates {min, lower-quantile, median, upper-quantile, max} from the sorted data array (ascending). Approximately median-unbiased regardless of the sample distribution (R8).
Parameters
Double[] data

Sample array, must be sorted ascendingly.

Single[] FiveNumberSummary(Single[] data)

Estimates {min, lower-quantile, median, upper-quantile, max} from the sorted data array (ascending). Approximately median-unbiased regardless of the sample distribution (R8).
Parameters
Single[] data

Sample array, must be sorted ascendingly.

double InterquartileRange(Double[] data)

Estimates the inter-quartile range from the sorted data array (ascending). Approximately median-unbiased regardless of the sample distribution (R8).
Parameters
Double[] data

Sample array, must be sorted ascendingly.

float InterquartileRange(Single[] data)

Estimates the inter-quartile range from the sorted data array (ascending). Approximately median-unbiased regardless of the sample distribution (R8).
Parameters
Single[] data

Sample array, must be sorted ascendingly.

float LowerQuartile(Single[] data)

Estimates the first quartile value from the sorted data array (ascending). Approximately median-unbiased regardless of the sample distribution (R8).
Parameters
Single[] data

Sample array, must be sorted ascendingly.

double LowerQuartile(Double[] data)

Estimates the first quartile value from the sorted data array (ascending). Approximately median-unbiased regardless of the sample distribution (R8).
Parameters
Double[] data

Sample array, must be sorted ascendingly.

double Maximum(Double[] data)

Returns the largest value from the sorted data array (ascending).
Parameters
Double[] data

Sample array, must be sorted ascendingly.

float Maximum(Single[] data)

Returns the largest value from the sorted data array (ascending).
Parameters
Single[] data

Sample array, must be sorted ascendingly.

float Median(Single[] data)

Estimates the median value from the sorted data array (ascending). Approximately median-unbiased regardless of the sample distribution (R8).
Parameters
Single[] data

Sample array, must be sorted ascendingly.

double Median(Double[] data)

Estimates the median value from the sorted data array (ascending). Approximately median-unbiased regardless of the sample distribution (R8).
Parameters
Double[] data

Sample array, must be sorted ascendingly.

float Minimum(Single[] data)

Returns the smallest value from the sorted data array (ascending).
Parameters
Single[] data

Sample array, must be sorted ascendingly.

double Minimum(Double[] data)

Returns the smallest value from the sorted data array (ascending).
Parameters
Double[] data

Sample array, must be sorted ascendingly.

float OrderStatistic(Single[] data, int order)

Returns the order statistic (order 1..N) from the sorted data array (ascending).
Parameters
Single[] data

Sample array, must be sorted ascendingly.

int order

One-based order of the statistic, must be between 1 and N (inclusive).

double OrderStatistic(Double[] data, int order)

Returns the order statistic (order 1..N) from the sorted data array (ascending).
Parameters
Double[] data

Sample array, must be sorted ascendingly.

int order

One-based order of the statistic, must be between 1 and N (inclusive).

float Percentile(Single[] data, int p)

Estimates the p-Percentile value from the sorted data array (ascending). If a non-integer Percentile is needed, use Quantile instead. Approximately median-unbiased regardless of the sample distribution (R8).
Parameters
Single[] data

Sample array, must be sorted ascendingly.

int p

Percentile selector, between 0 and 100 (inclusive).

double Percentile(Double[] data, int p)

Estimates the p-Percentile value from the sorted data array (ascending). If a non-integer Percentile is needed, use Quantile instead. Approximately median-unbiased regardless of the sample distribution (R8).
Parameters
Double[] data

Sample array, must be sorted ascendingly.

int p

Percentile selector, between 0 and 100 (inclusive).

float Quantile(Single[] data, double tau)

Estimates the tau-th quantile from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution function crosses tau. Approximately median-unbiased regardless of the sample distribution (R8).
R-8, SciPy-(1/3,1/3): Linear interpolation of the approximate medians for order statistics. When tau < (2/3) / (N + 1/3), use x1. When tau >= (N - 1/3) / (N + 1/3), use xN.
Parameters
Single[] data

Sample array, must be sorted ascendingly.

double tau

Quantile selector, between 0.0 and 1.0 (inclusive).

double Quantile(Double[] data, double tau)

Estimates the tau-th quantile from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution function crosses tau. Approximately median-unbiased regardless of the sample distribution (R8).
R-8, SciPy-(1/3,1/3): Linear interpolation of the approximate medians for order statistics. When tau < (2/3) / (N + 1/3), use x1. When tau >= (N - 1/3) / (N + 1/3), use xN.
Parameters
Double[] data

Sample array, must be sorted ascendingly.

double tau

Quantile selector, between 0.0 and 1.0 (inclusive).

float QuantileCustom(Single[] data, double tau, QuantileDefinition definition)

Estimates the tau-th quantile from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution function crosses tau. The quantile definition can be specified to be compatible with an existing system.
Parameters
Single[] data

Sample array, must be sorted ascendingly.

double tau

Quantile selector, between 0.0 and 1.0 (inclusive).

QuantileDefinition definition

Quantile definition, to choose what product/definition it should be consistent with

double QuantileCustom(Double[] data, double tau, double a, double b, double c, double d)

Estimates the tau-th quantile from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution function crosses tau. The quantile defintion can be specified by 4 parameters a, b, c and d, consistent with Mathematica.
Parameters
Double[] data

Sample array, must be sorted ascendingly.

double tau

Quantile selector, between 0.0 and 1.0 (inclusive).

double a

a-parameter

double b

b-parameter

double c

c-parameter

double d

d-parameter

double QuantileCustom(Double[] data, double tau, QuantileDefinition definition)

Estimates the tau-th quantile from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution function crosses tau. The quantile definition can be specified to be compatible with an existing system.
Parameters
Double[] data

Sample array, must be sorted ascendingly.

double tau

Quantile selector, between 0.0 and 1.0 (inclusive).

QuantileDefinition definition

Quantile definition, to choose what product/definition it should be consistent with

float QuantileCustom(Single[] data, double tau, double a, double b, double c, double d)

Estimates the tau-th quantile from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution function crosses tau. The quantile defintion can be specified by 4 parameters a, b, c and d, consistent with Mathematica.
Parameters
Single[] data

Sample array, must be sorted ascendingly.

double tau

Quantile selector, between 0.0 and 1.0 (inclusive).

double a

a-parameter

double b

b-parameter

double c

c-parameter

double d

d-parameter

double QuantileRank(Double[] data, double x, RankDefinition definition)

Estimates the quantile tau from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution function crosses tau. The quantile definition can be specified to be compatible with an existing system.
Parameters
Double[] data

The data sample sequence.

double x

Quantile value.

RankDefinition definition

Rank definition, to choose how ties should be handled and what product/definition it should be consistent with

double QuantileRank(Single[] data, float x, RankDefinition definition)

Estimates the quantile tau from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution function crosses tau. The quantile definition can be specified to be compatible with an existing system.
Parameters
Single[] data

The data sample sequence.

float x

Quantile value.

RankDefinition definition

Rank definition, to choose how ties should be handled and what product/definition it should be consistent with

Double[] Ranks(Single[] data, RankDefinition definition)

Evaluates the rank of each entry of the sorted data array (ascending). The rank definition can be specified to be compatible with an existing system.

Double[] Ranks(Double[] data, RankDefinition definition)

Evaluates the rank of each entry of the sorted data array (ascending). The rank definition can be specified to be compatible with an existing system.

float UpperQuartile(Single[] data)

Estimates the third quartile value from the sorted data array (ascending). Approximately median-unbiased regardless of the sample distribution (R8).
Parameters
Single[] data

Sample array, must be sorted ascendingly.

double UpperQuartile(Double[] data)

Estimates the third quartile value from the sorted data array (ascending). Approximately median-unbiased regardless of the sample distribution (R8).
Parameters
Double[] data

Sample array, must be sorted ascendingly.