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Statistics Class

Extension methods to return basic statistics on set of data.
Inheritance Hierarchy
SystemObject
  Altaxo.Calc.StatisticsStatistics

Namespace: Altaxo.Calc.Statistics
Assembly: AltaxoCore (in AltaxoCore.dll) Version: 4.8.3179.0 (4.8.3179.0)
Syntax
C#
public static class Statistics

The Statistics type exposes the following members.

Methods
 NameDescription
Public Extension MethodCovariance(IEnumerableDouble, IEnumerableDouble) Estimates the unbiased population covariance from the provided samples. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN.
Public Extension MethodCovariance(IEnumerableNullableDouble, IEnumerableNullableDouble) Estimates the unbiased population covariance from the provided samples. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN. Null-entries are ignored.
Public Extension MethodCovariance(IEnumerableSingle, IEnumerableSingle) Estimates the unbiased population covariance from the provided samples. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN.
Public Extension MethodEmpiricalCDF(IEnumerableDouble, Double) Estimates the empirical cumulative distribution function (CDF) at x from the provided samples.
Public Extension MethodEmpiricalCDF(IEnumerableNullableDouble, Double) Estimates the empirical cumulative distribution function (CDF) at x from the provided samples.
Public Extension MethodEmpiricalCDF(IEnumerableSingle, Single) Estimates the empirical cumulative distribution function (CDF) at x from the provided samples.
Public Extension MethodEmpiricalCDFFunc(IEnumerableDouble) Estimates the empirical cumulative distribution function (CDF) at x from the provided samples.
Public Extension MethodEmpiricalCDFFunc(IEnumerableNullableDouble) Estimates the empirical cumulative distribution function (CDF) at x from the provided samples.
Public Extension MethodEmpiricalCDFFunc(IEnumerableSingle) Estimates the empirical cumulative distribution function (CDF) at x from the provided samples.
Public Extension MethodEmpiricalInvCDF(IEnumerableDouble, Double) Estimates the empirical inverse CDF at tau from the provided samples.
Public Extension MethodEmpiricalInvCDF(IEnumerableNullableDouble, Double) Estimates the empirical inverse CDF at tau from the provided samples.
Public Extension MethodEmpiricalInvCDF(IEnumerableSingle, Double) Estimates the empirical inverse CDF at tau from the provided samples.
Public Extension MethodEmpiricalInvCDFFunc(IEnumerableDouble) Estimates the empirical inverse CDF at tau from the provided samples.
Public Extension MethodEmpiricalInvCDFFunc(IEnumerableNullableDouble) Estimates the empirical inverse CDF at tau from the provided samples.
Public Extension MethodEmpiricalInvCDFFunc(IEnumerableSingle) Estimates the empirical inverse CDF at tau from the provided samples.
Public methodStatic memberEntropy(IEnumerableDouble) Calculates the entropy of a stream of double values in bits. Returns NaN if any of the values in the stream are NaN.
Public methodStatic memberEntropy(IEnumerableNullableDouble) Calculates the entropy of a stream of double values in bits. Returns NaN if any of the values in the stream are NaN. Null-entries are ignored.
Public Extension MethodFiveNumberSummary(IEnumerableDouble) Estimates {min, lower-quantile, median, upper-quantile, max} from the provided samples. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodFiveNumberSummary(IEnumerableNullableDouble) Estimates {min, lower-quantile, median, upper-quantile, max} from the provided samples. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodFiveNumberSummary(IEnumerableSingle) Estimates {min, lower-quantile, median, upper-quantile, max} from the provided samples. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodGeometricMean(IEnumerableDouble) Evaluates the geometric mean. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodGeometricMean(IEnumerableSingle) Evaluates the geometric mean. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodHarmonicMean(IEnumerableDouble) Evaluates the harmonic mean. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodHarmonicMean(IEnumerableSingle) Evaluates the harmonic mean. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodInterquartileRange(IEnumerableDouble) Estimates the inter-quartile range from the provided samples. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodInterquartileRange(IEnumerableNullableDouble) Estimates the inter-quartile range from the provided samples. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodInterquartileRange(IEnumerableSingle) Estimates the inter-quartile range from the provided samples. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodKurtosis(IEnumerableDouble) Estimates the unbiased population kurtosis from the provided samples. Uses a normalizer (Bessel's correction; type 2). Returns NaN if data has less than four entries or if any entry is NaN.
Public Extension MethodKurtosis(IEnumerableNullableDouble) Estimates the unbiased population kurtosis from the provided samples. Uses a normalizer (Bessel's correction; type 2). Returns NaN if data has less than four entries or if any entry is NaN. Null-entries are ignored.
Public Extension MethodLowerQuartile(IEnumerableDouble) Estimates the first quartile value from the provided samples. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodLowerQuartile(IEnumerableNullableDouble) Estimates the first quartile value from the provided samples. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodLowerQuartile(IEnumerableSingle) Estimates the first quartile value from the provided samples. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodMaximum(IEnumerableDouble) Returns the maximum value in the sample data. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodMaximum(IEnumerableNullableDouble) Returns the maximum value in the sample data. Returns NaN if data is empty or if any entry is NaN. Null-entries are ignored.
Public Extension MethodMaximum(IEnumerableSingle) Returns the maximum value in the sample data. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodMaximumAbsolute(IEnumerableDouble) Returns the maximum absolute value in the sample data. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodMaximumAbsolute(IEnumerableSingle) Returns the maximum absolute value in the sample data. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodMaximumMagnitudePhase(IEnumerableComplex32) Returns the maximum magnitude and phase value in the sample data. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodMaximumMagnitudePhase(IEnumerableComplex) Returns the maximum magnitude and phase value in the sample data. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodMean(IEnumerableDouble) Evaluates the sample mean, an estimate of the population mean. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodMean(IEnumerableNullableDouble) Evaluates the sample mean, an estimate of the population mean. Returns NaN if data is empty or if any entry is NaN. Null-entries are ignored.
Public Extension MethodMean(IEnumerableSingle) Evaluates the sample mean, an estimate of the population mean. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodMeanStandardDeviation(IEnumerableDouble) Estimates the sample mean and the unbiased population standard deviation from the provided samples. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN for mean if data is empty or if any entry is NaN and NaN for standard deviation if data has less than two entries or if any entry is NaN.
Public Extension MethodMeanStandardDeviation(IEnumerableSingle) Estimates the sample mean and the unbiased population standard deviation from the provided samples. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN for mean if data is empty or if any entry is NaN and NaN for standard deviation if data has less than two entries or if any entry is NaN.
Public Extension MethodMeanVariance(IEnumerableDouble) Estimates the sample mean and the unbiased population variance from the provided samples. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN for mean if data is empty or if any entry is NaN and NaN for variance if data has less than two entries or if any entry is NaN.
Public Extension MethodMeanVariance(IEnumerableSingle) Estimates the sample mean and the unbiased population variance from the provided samples. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN for mean if data is empty or if any entry is NaN and NaN for variance if data has less than two entries or if any entry is NaN.
Public Extension MethodMedian(IEnumerableDouble) Estimates the sample median from the provided samples (R8).
Public Extension MethodMedian(IEnumerableNullableDouble) Estimates the sample median from the provided samples (R8).
Public Extension MethodMedian(IEnumerableSingle) Estimates the sample median from the provided samples (R8).
Public Extension MethodMinimum(IEnumerableDouble) Returns the minimum value in the sample data. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodMinimum(IEnumerableNullableDouble) Returns the minimum value in the sample data. Returns NaN if data is empty or if any entry is NaN. Null-entries are ignored.
Public Extension MethodMinimum(IEnumerableSingle) Returns the minimum value in the sample data. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodMinimumAbsolute(IEnumerableDouble) Returns the minimum absolute value in the sample data. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodMinimumAbsolute(IEnumerableSingle) Returns the minimum absolute value in the sample data. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodMinimumMagnitudePhase(IEnumerableComplex32) Returns the minimum magnitude and phase value in the sample data. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodMinimumMagnitudePhase(IEnumerableComplex) Returns the minimum magnitude and phase value in the sample data. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodMovingAverage Evaluates the sample mean over a moving window, for each samples. Returns NaN if no data is empty or if any entry is NaN.
Public methodStatic memberOrderStatistic(IEnumerableDouble, Int32) Returns the order statistic (order 1..N) from the provided samples.
Public methodStatic memberOrderStatistic(IEnumerableSingle, Int32) Returns the order statistic (order 1..N) from the provided samples.
Public methodStatic memberOrderStatisticFunc(IEnumerableDouble) Returns the order statistic (order 1..N) from the provided samples.
Public methodStatic memberOrderStatisticFunc(IEnumerableSingle) Returns the order statistic (order 1..N) from the provided samples.
Public Extension MethodPercentile(IEnumerableDouble, Int32) Estimates the p-Percentile value from the provided samples. If a non-integer Percentile is needed, use Quantile instead. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodPercentile(IEnumerableNullableDouble, Int32) Estimates the p-Percentile value from the provided samples. If a non-integer Percentile is needed, use Quantile instead. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodPercentile(IEnumerableSingle, Int32) Estimates the p-Percentile value from the provided samples. If a non-integer Percentile is needed, use Quantile instead. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodPercentileFunc(IEnumerableDouble) Estimates the p-Percentile value from the provided samples. If a non-integer Percentile is needed, use Quantile instead. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodPercentileFunc(IEnumerableNullableDouble) Estimates the p-Percentile value from the provided samples. If a non-integer Percentile is needed, use Quantile instead. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodPercentileFunc(IEnumerableSingle) Estimates the p-Percentile value from the provided samples. If a non-integer Percentile is needed, use Quantile instead. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodPopulationCovariance(IEnumerableDouble, IEnumerableDouble) Evaluates the population covariance from the provided full populations. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodPopulationCovariance(IEnumerableNullableDouble, IEnumerableNullableDouble) Evaluates the population covariance from the provided full populations. On a dataset of size N will use an N normalize and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN. Null-entries are ignored.
Public Extension MethodPopulationCovariance(IEnumerableSingle, IEnumerableSingle) Evaluates the population covariance from the provided full populations. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodPopulationKurtosis(IEnumerableDouble) Evaluates the kurtosis from the full population. Does not use a normalizer and would thus be biased if applied to a subset (type 1). Returns NaN if data has less than three entries or if any entry is NaN.
Public Extension MethodPopulationKurtosis(IEnumerableNullableDouble) Evaluates the kurtosis from the full population. Does not use a normalizer and would thus be biased if applied to a subset (type 1). Returns NaN if data has less than three entries or if any entry is NaN. Null-entries are ignored.
Public Extension MethodPopulationSkewness(IEnumerableDouble) Evaluates the skewness from the full population. Does not use a normalizer and would thus be biased if applied to a subset (type 1). Returns NaN if data has less than two entries or if any entry is NaN.
Public Extension MethodPopulationSkewness(IEnumerableNullableDouble) Evaluates the skewness from the full population. Does not use a normalizer and would thus be biased if applied to a subset (type 1). Returns NaN if data has less than two entries or if any entry is NaN. Null-entries are ignored.
Public Extension MethodPopulationSkewnessKurtosis Evaluates the skewness and kurtosis from the full population. Does not use a normalizer and would thus be biased if applied to a subset (type 1).
Public Extension MethodPopulationStandardDeviation(IEnumerableDouble) Evaluates the standard deviation from the provided full population. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodPopulationStandardDeviation(IEnumerableNullableDouble) Evaluates the standard deviation from the provided full population. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN. Null-entries are ignored.
Public Extension MethodPopulationStandardDeviation(IEnumerableSingle) Evaluates the standard deviation from the provided full population. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodPopulationVariance(IEnumerableDouble) Evaluates the variance from the provided full population. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodPopulationVariance(IEnumerableNullableDouble) Evaluates the variance from the provided full population. On a dataset of size N will use an N normalize and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN. Null-entries are ignored.
Public Extension MethodPopulationVariance(IEnumerableSingle) Evaluates the variance from the provided full population. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodQuantile(IEnumerableDouble, Double) Estimates the tau-th quantile from the provided samples. The tau-th quantile is the data value where the cumulative distribution function crosses tau. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodQuantile(IEnumerableNullableDouble, Double) Estimates the tau-th quantile from the provided samples. The tau-th quantile is the data value where the cumulative distribution function crosses tau. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodQuantile(IEnumerableSingle, Double) Estimates the tau-th quantile from the provided samples. The tau-th quantile is the data value where the cumulative distribution function crosses tau. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodQuantileCustom(IEnumerableDouble, Double, QuantileDefinition) Estimates the tau-th quantile from the provided samples. 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.
Public Extension MethodQuantileCustom(IEnumerableNullableDouble, Double, QuantileDefinition) Estimates the tau-th quantile from the provided samples. 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.
Public Extension MethodQuantileCustom(IEnumerableSingle, Double, QuantileDefinition) Estimates the tau-th quantile from the provided samples. 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.
Public Extension MethodQuantileCustomFunc(IEnumerableDouble, QuantileDefinition) Estimates the tau-th quantile from the provided samples. 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.
Public Extension MethodQuantileCustomFunc(IEnumerableNullableDouble, QuantileDefinition) Estimates the tau-th quantile from the provided samples. 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.
Public Extension MethodQuantileCustomFunc(IEnumerableSingle, QuantileDefinition) Estimates the tau-th quantile from the provided samples. 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.
Public Extension MethodQuantileFunc(IEnumerableDouble) Estimates the tau-th quantile from the provided samples. The tau-th quantile is the data value where the cumulative distribution function crosses tau. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodQuantileFunc(IEnumerableNullableDouble) Estimates the tau-th quantile from the provided samples. The tau-th quantile is the data value where the cumulative distribution function crosses tau. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodQuantileFunc(IEnumerableSingle) Estimates the tau-th quantile from the provided samples. The tau-th quantile is the data value where the cumulative distribution function crosses tau. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodQuantileRank(IEnumerableDouble, Double, RankDefinition) Estimates the quantile tau from the provided samples. 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.
Public Extension MethodQuantileRank(IEnumerableNullableDouble, Double, RankDefinition) Estimates the quantile tau from the provided samples. 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.
Public Extension MethodQuantileRank(IEnumerableSingle, Single, RankDefinition) Estimates the quantile tau from the provided samples. 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.
Public Extension MethodQuantileRankFunc(IEnumerableDouble, RankDefinition) Estimates the quantile tau from the provided samples. 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.
Public Extension MethodQuantileRankFunc(IEnumerableNullableDouble, RankDefinition) Estimates the quantile tau from the provided samples. 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.
Public Extension MethodQuantileRankFunc(IEnumerableSingle, RankDefinition) Estimates the quantile tau from the provided samples. 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.
Public Extension MethodRanks(IEnumerableDouble, RankDefinition) Evaluates the rank of each entry of the provided samples. The rank definition can be specified to be compatible with an existing system.
Public Extension MethodRanks(IEnumerableNullableDouble, RankDefinition) Evaluates the rank of each entry of the provided samples. The rank definition can be specified to be compatible with an existing system.
Public Extension MethodRanks(IEnumerableSingle, RankDefinition) Evaluates the rank of each entry of the provided samples. The rank definition can be specified to be compatible with an existing system.
Public Extension MethodRootMeanSquare(IEnumerableDouble) Evaluates the root mean square (RMS) also known as quadratic mean. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodRootMeanSquare(IEnumerableNullableDouble) Evaluates the root mean square (RMS) also known as quadratic mean. Returns NaN if data is empty or if any entry is NaN. Null-entries are ignored.
Public Extension MethodRootMeanSquare(IEnumerableSingle) Evaluates the root mean square (RMS) also known as quadratic mean. Returns NaN if data is empty or if any entry is NaN.
Public Extension MethodSkewness(IEnumerableDouble) Estimates the unbiased population skewness from the provided samples. Uses a normalizer (Bessel's correction; type 2). Returns NaN if data has less than three entries or if any entry is NaN.
Public Extension MethodSkewness(IEnumerableNullableDouble) Estimates the unbiased population skewness from the provided samples. Uses a normalizer (Bessel's correction; type 2). Returns NaN if data has less than three entries or if any entry is NaN. Null-entries are ignored.
Public Extension MethodSkewnessKurtosis Estimates the unbiased population skewness and kurtosis from the provided samples in a single pass. Uses a normalizer (Bessel's correction; type 2).
Public Extension MethodStandardDeviation(IEnumerableDouble) Estimates the unbiased population standard deviation from the provided samples. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN.
Public Extension MethodStandardDeviation(IEnumerableNullableDouble) Estimates the unbiased population standard deviation from the provided samples. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN. Null-entries are ignored.
Public Extension MethodStandardDeviation(IEnumerableSingle) Estimates the unbiased population standard deviation from the provided samples. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN.
Public Extension MethodUpperQuartile(IEnumerableDouble) Estimates the third quartile value from the provided samples. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodUpperQuartile(IEnumerableNullableDouble) Estimates the third quartile value from the provided samples. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodUpperQuartile(IEnumerableSingle) Estimates the third quartile value from the provided samples. Approximately median-unbiased regardless of the sample distribution (R8).
Public Extension MethodVariance(IEnumerableDouble) Estimates the unbiased population variance from the provided samples. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN.
Public Extension MethodVariance(IEnumerableNullableDouble) Estimates the unbiased population variance from the provided samples. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN. Null-entries are ignored.
Public Extension MethodVariance(IEnumerableSingle) Estimates the unbiased population variance from the provided samples. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN.
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