public sealed class Sample : ICollection<double>,
IEnumerable<double>, IEnumerable, IReadOnlyCollection<double>,
IReadOnlyList<double>
Public NotInheritable Class Sample
Implements ICollection(Of Double), IEnumerable(Of Double),
IEnumerable, IReadOnlyCollection(Of Double), IReadOnlyList(Of Double)
public ref class Sample sealed : ICollection<double>,
IEnumerable<double>, IEnumerable, IReadOnlyCollection<double>,
IReadOnlyList<double>
[<SealedAttribute>]
type Sample =
class
interface ICollection<float>
interface IEnumerable<float>
interface IEnumerable
interface IReadOnlyCollection<float>
interface IReadOnlyList<float>
end
A univariate sample is a data set which records one number for each independent observation. For example, data from a study which measured the weight of each subject could be stored in the Sample class. The class offers descriptive statistics for the sample, estimates of descriptive statistics of the underlying population distribution, and statistical tests to compare the sample distribution to other sample distributions or theoretical models.
NOTE: This class will be retired in a future release. Its functionality is replaced by the Univariate class, which can operatate on arbitrary data lists.
Sample | Initializes a new, empty sample. |
Sample(Double) | Initializes a new sample from a list of values. |
Sample(IEnumerableDouble) | Initializes a new sample from a list of values. |
Sample(String) | Initializes a new, empty sample with the given name. |
CorrectedStandardDeviation | Gets the Bessel-corrected standard deviation. |
Count | Gets the number of values in the sample. |
InterquartileRange | Gets the interquartile range of sample measurements. |
IsReadOnly | Gets a value indicating whether the sample is read-only. |
Maximum | Gets the largest value in the sample. |
Mean | Gets the sample mean. |
Median | Gets the sample median. |
Minimum | Gets the smallest value in the sample. |
Name | Gets or sets the name of the sample. |
PopulationMean | Gets an estimate of the population mean from the sample. |
PopulationStandardDeviation | Gets an estimate of the population standard deviation from the sample. |
PopulationVariance | Gets an estimate of the population variance from the sample. |
Skewness | Gets the sample skewness. |
StandardDeviation | Gets the sample standard deviation. |
Variance | Gets the sample variance. |
Add(Double) | Adds a value to the sample. |
Add(Double) | Adds multiple values to the sample. |
Add(IEnumerableDouble) | Adds multiple values to the sample. |
CentralMoment | Computes the given sample central moment. |
Clear | Remove all values from the sample. |
Contains | Determines whether the sample contains the given value. |
Copy | Copies the sample. |
Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) |
FisherFTest | Tests whether the variances of two samples are compatible. |
GetEnumerator | Gets an enumerator of sample values. |
GetHashCode | Serves as the default hash function. (Inherited from Object) |
GetType | Gets the Type of the current instance. (Inherited from Object) |
InverseLeftProbability | Gets the sample value corresponding to a given percentile score. |
KolmogorovSmirnovTest(ContinuousDistribution) | Tests whether the sample is compatible with the given distribution. |
KolmogorovSmirnovTest(Sample, Sample) | Tests whether the sample is compatible with another sample. |
KruskalWallisTest(IReadOnlyListSample) | Performs a Kruskal-Wallis test on the given samples. |
KruskalWallisTest(Sample) | Performs a Kruskal-Wallis test on the given samples. |
KuiperTest | Tests whether the sample is compatible with the given distribution. |
LeftProbability | Gets the fraction of values equal to or less than the given value. |
MannWhitneyTest | Tests whether one sample median is compatible with another sample median. |
MaximumLikelihoodFit | Performs a maximum likelihood fit. |
OneWayAnovaTest(IReadOnlyCollectionSample) | Performs a one-way analysis of variance (ANOVA). |
OneWayAnovaTest(Sample) | Performs a one-way analysis of variance (ANOVA). |
PopulationCentralMoment | Estimates the given population central moment from the sample. |
PopulationRawMoment | Estimates the given population raw moment from the sample. |
RawMoment | Computes the given sample raw moment. |
Remove | Removes a given value from the sample. |
ShapiroFranciaTest | Performs a Shapiro-Francia test of normality on the sample. |
SignTest | Tests whether the sample median is compatible with the given reference value. |
StudentTTest(Double) | Tests whether the sample mean is compatible with the reference mean. |
StudentTTest(Sample, Sample) | Tests whether one sample mean is compatible with another sample mean. |
ToString | Returns a string that represents the current object. (Inherited from Object) |
Transform | Transforms all values using a user-supplied function. |
TwoWayAnovaTest | Performs a two-way analysis of variance. |
ZTest | Performs a z-test. |
Autocovariance |
Computes the auto-covariance for all lags.
(Defined by Series) |
Autocovariance |
Computes the auto-covariance of the series at the given lag.
(Defined by Series) |
CentralMoment |
Computes the given sample central moment.
(Defined by Univariate) |
CorrectedStandardDeviation |
Computes the Bessel-corrected standard deviation.
(Defined by Univariate) |
CorrelationCoefficient |
Computes the correlation coefficient between the two variables.
(Defined by Bivariate) |
Covariance |
Computes the covariance of the two variables.
(Defined by Bivariate) |
FitToAR1 |
Fits an AR(1) model to the time series.
(Defined by Series) |
FitToBeta |
Finds the Beta distribution that best fits the given sample.
(Defined by Univariate) |
FitToExponential |
Finds the exponential distribution that best fits the given sample.
(Defined by Univariate) |
FitToGamma |
Finds the Gamma distribution that best fits the given sample.
(Defined by Univariate) |
FitToGumbel |
Find the Gumbel distribution that best fit the given sample.
(Defined by Univariate) |
FitToLognormal |
Finds the log-normal distribution that best fits the given sample.
(Defined by Univariate) |
FitToMA1 |
Fits an MA(1) model to the time series.
(Defined by Series) |
FitToNormal |
Finds the normal distribution that best fits the given sample.
(Defined by Univariate) |
FitToRayleigh |
Finds the Rayleigh distribution that best fits the given sample.
(Defined by Univariate) |
FitToWald |
Finds the Wald distribution that best fits a sample.
(Defined by Univariate) |
FitToWeibull |
Finds the Weibull distribution that best fits the given sample.
(Defined by Univariate) |
InterquartileRange |
Finds the interquartile range.
(Defined by Univariate) |
InverseLeftProbability |
Finds the sample value corresponding to a given percentile.
(Defined by Univariate) |
KolmogorovSmirnovTest |
Tests whether the sample is compatible with the given distribution.
(Defined by Univariate) |
KuiperTest |
Tests whether the sample is compatible with the given distribution.
(Defined by Univariate) |
LeftProbability |
Gets the fraction of values equal to or less than the given value.
(Defined by Univariate) |
LinearRegression |
Computes the best-fit linear regression from the data.
(Defined by Bivariate) |
LjungBoxTest |
Performs a Ljung-Box test for non-correlation.
(Defined by Series) |
LjungBoxTest |
Performs a Ljung-Box test for non-correlation with the given number of lags.
(Defined by Series) |
Maximum |
Finds the maximum value.
(Defined by Univariate) |
MaximumLikelihoodFit |
Finds the parameters that make an arbitrary, parameterized distribution best fit the sample.
(Defined by Univariate) |
Mean |
Computes the sample mean.
(Defined by Univariate) |
Median |
Finds the median.
(Defined by Univariate) |
Minimum |
Finds the minimum value.
(Defined by Univariate) |
MultiLinearRegression |
Performs a multivariate linear regression on the named columns.
(Defined by Multivariate) |
MultiLinearRegression |
Performs a multivariate linear regression.
(Defined by Multivariate) |
NonlinearRegression |
Finds the parameterized function that best fits the data.
(Defined by Bivariate) |
NonlinearRegression |
Finds the parameterized function that best fits the data.
(Defined by Bivariate) |
PolynomialRegression |
Computes the polynomial of given degree which best fits the data.
(Defined by Bivariate) |
PopulationCentralMoment |
Estimates the given central moment of the underlying population.
(Defined by Univariate) |
PopulationCovariance |
Estimates the covariance of the two variables in the population.
(Defined by Bivariate) |
PopulationMean |
Estimates the mean of the underlying population.
(Defined by Univariate) |
PopulationRawMoment |
Estimates the given raw moment of the underlying population.
(Defined by Univariate) |
PopulationStandardDeviation |
Estimates of the standard deviation of the underlying population.
(Defined by Univariate) |
PopulationVariance |
Estimates of the variance of the underlying population.
(Defined by Univariate) |
PowerSpectrum |
Computes the power spectrum of the time series.
(Defined by Series) |
RawMoment |
Computes the given sample raw moment.
(Defined by Univariate) |
SeriesPopulationStatistics |
Computes estimates for the moments of the population from which the time series is drawn.
(Defined by Series) |
ShapiroFranciaTest |
Performs a Shapiro-Francia test of normality on the sample.
(Defined by Univariate) |
SignTest |
Tests whether the sample median is compatible with the given reference value.
(Defined by Univariate) |
Skewness |
Computes the sample skewness.
(Defined by Univariate) |
StandardDeviation |
Computes the sample standard deviation.
(Defined by Univariate) |
StudentTTest |
Tests whether the sample mean is compatible with the reference mean.
(Defined by Univariate) |
Trimean |
Finds the tri-mean.
(Defined by Univariate) |
Variance |
Computes the sample variance.
(Defined by Univariate) |
ZTest |
Performs a z-test to test whether the given sample is compatible with the given normal reference population.
(Defined by Univariate) |