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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(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 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[] 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.
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.
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.
float Maximum(Single[] data)
Returns the largest value from the sorted data array (ascending).
Parameters
Single[] 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.
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 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 Minimum(Double[] data)
Returns the smallest value from the sorted data array (ascending).
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.
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).
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).
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 definition 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
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 definition 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
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).
Quantile definition, to choose what product/definition it should be consistent with
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.
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.
Rank definition, to choose how ties should be handled and what product/definition it should be consistent with
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.
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 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.
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.
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