Series Class |
public sealed class Series : Series<Date>, IAdditionOperators<Series, Series, Series>, IAdditionOperators<Series, double, Series>, ISubtractionOperators<Series, Series, Series>, ISubtractionOperators<Series, double, Series>, IMultiplyOperators<Series, double, Series>, IDivisionOperators<Series, double, Series>, IUnaryNegationOperators<Series, Series>, IPointwiseOperators<Series>, IFormattable
The Series type exposes the following members.
| Name | Description | |
|---|---|---|
| Series(String, String, Double, Series) | Creates a named time series. | |
| Series(String, String, Date, Double, Series) | Creates a named time series. | |
| Series(String, String, Date, Double, SeriesType, Frequency) | Creates a named time series. |
| Name | Description | |
|---|---|---|
| Args | Gets the list of arguments from the series. (Inherited from SeriesT) | |
| Count | Gets the number of points in the series. (Inherited from SeriesT) | |
| Dates | Gets dates from the series as a vector. | |
| EnumValues | Gets the list of values from the series. (Inherited from SeriesT) | |
| First | Gets the first point in the series. (Inherited from SeriesT) | |
| Freq | Gets the sampling frequency. | |
| ItemIndex | Gets a point given its index. (Inherited from SeriesT) | |
| ItemInt32 | Gets a point given its index. (Inherited from SeriesT) | |
| ItemRange | Extracts a slice from the series. | |
| Kurtosis | Gets the unbiased population kurtosis. (Inherited from SeriesT) | |
| Last | Gets the last point in the series. (Inherited from SeriesT) | |
| Maximum | Returns the maximum value from the series. (Inherited from SeriesT) | |
| Mean | Gets the mean value from the series. (Inherited from SeriesT) | |
| Minimum | Returns the minimum value from the series. (Inherited from SeriesT) | |
| Name | Gets the name of the series. (Inherited from SeriesT) | |
| Points | Gets the sorted list of points. (Inherited from SeriesT) | |
| PopulationKurtosis | Gets the kurtosis from the full population. (Inherited from SeriesT) | |
| PopulationSkewness | Get the skewness from the full population. (Inherited from SeriesT) | |
| PopulationStandardDeviation | Gets the standard deviation from the full population. (Inherited from SeriesT) | |
| PopulationVariance | Gets the variance from the full population. (Inherited from SeriesT) | |
| Skewness | Gets the unbiased population skewness. (Inherited from SeriesT) | |
| StandardDeviation | Gets the unbiased standard deviation. (Inherited from SeriesT) | |
| Stats | Gets statistics on the series. (Inherited from SeriesT) | |
| Tag | A custom tag for the series. | |
| Ticker | Gets the ticker of the series. (Inherited from SeriesT) | |
| Type | Is this a raw (Prices) series or a derived one? (Inherited from SeriesT) | |
| Values | Gets the values array as a vector. (Inherited from SeriesT) | |
| Variance | Gets the unbiased variance. (Inherited from SeriesT) |
| Name | Description | |
|---|---|---|
| AbsMax | Gets the maximum absolute value. (Inherited from SeriesT) | |
| AbsMin | Gets the minimum absolute value. (Inherited from SeriesT) | |
| ACF | Computes autocorrelation for all lags. (Inherited from SeriesT) | |
| Adapt | Transforms a SeriesT into a Series. | |
| All | Checks whether the predicate is satisfied by all items. | |
| Any | Checks whether the predicate is satisfied by at least one item. | |
| ARModel | Creates an AR model from a series and a degree. | |
| AsLogReturns | Creates a new series based in the logarithmic returns. | |
| AsReturns | Creates a new series based in the returns. | |
| AutoCorrelation | Computes the autocorrelation for a fixed lag. (Inherited from SeriesT) | |
| AutoRegression | Finds the coefficients for an autoregressive model. (Inherited from SeriesT) | |
| Combine | Calculates the weighted sum of an array of series. | |
| Contains(Date) | Checks if the series contains the given value. | |
| Contains(Double) | Checks if the series contains the given value. (Inherited from SeriesT) | |
| Correlation | Computes the Pearson correlation between two series. (Inherited from SeriesT) | |
| Correlogram | Computes autocorrelation for a range of lags. (Inherited from SeriesT) | |
| Covariance | Computes the covariance between two series. (Inherited from SeriesT) | |
| Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) | |
| EWMA | Smooths data using a exponentially weighted moving average. | |
| Fft | Computes the real discrete Fourier transform. (Inherited from SeriesT) | |
| Filter | Creates a new series by transforming each item with the given function. | |
| Fit | Gets linear coefficients for a fitting line. | |
| FromCsv(String, Csv, Int32, Int32) | Imports a series from a CSV file. | |
| FromCsv(String, Csv, String, String) | Imports a series from a CSV file. | |
| FullLinearModel | Creates a linear model from a series and a set of predictors. | |
| GetHashCode | Serves as the default hash function. (Inherited from Object) | |
| GetSliceStats(Date) | Gets statistics on a slice of a date series. | |
| GetSliceStats(T, T) | Gets statistics on a slice of the series. (Inherited from SeriesT) | |
| GetType | Gets the Type of the current instance. (Inherited from Object) | |
| IndexOf | Returns the zero-based index of the first occurrence of a value. (Inherited from SeriesT) | |
| LinearFit | Computes the series predicted by a linear fit. | |
| LinearModel | Multilinear regression based in Ordinary Least Squares. (Inherited from SeriesT) | |
| MAModel | Creates an MA model from a series and a degree. | |
| Map | Creates a new series by transforming each item with the given function. | |
| MovingAverage | Finds the coefficients for a moving average model. (Inherited from SeriesT) | |
| MovingAvg | Smooths data using a simple moving average. | |
| MovingNcdf | Compress data using a simple moving percentile. | |
| MovingRet | Gets the moving return of a one month window. | |
| MovingStd | Smooths data using a simple moving standard deviation. | |
| NCdf | The normal cumulative distribution function of the most recent value. (Inherited from SeriesT) | |
| NCdf(Double) | The normal cumulative distribution function. (Inherited from SeriesT) | |
| PACF | Computes the partial autocorrelation for all lags. (Inherited from SeriesT) | |
| Percentiles | Returns ascendenly sorted values. (Inherited from SeriesT) | |
| PointwiseDivide | Creates a new series by dividing values from the operands. | |
| PointwiseMultiply | Creates a new series by multiplying values from the operands. | |
| Prune | Creates a series retaining the first count items. | |
| Random | Generates a normally distributed series using statistics from this series. | |
| SafeThis |
Safe access to the series' points. If the index is out of range, a zero is returned.
(Inherited from SeriesT) | |
| SetName | Clones this series with a new name. | |
| Slice(Date, Date) | Takes a slice from a series. | |
| Slice(Int32, Int32) | Takes a slice from a series. | |
| Spline | Creates an interpolator for this series. | |
| Sum | Calculates the sum of the series values. (Inherited from SeriesT) | |
| ToString | Gets a textual representation of the series. (Overrides SeriesTToString) | |
| ToString(String, IFormatProvider) | Gets a textual representation of the series. | |
| Zip | Combines the common sufix of two time series. |
| Name | Description | |
|---|---|---|
| Addition(Double, Series) | Adds a scalar to a series. | |
| Addition(Series, Series) | Creates a new series by adding values from the operands. | |
| Addition(Series, Double) | Adds a scalar to a series. | |
| Division(Series, Double) | Divides all values from a series. | |
| Multiply(Double, Series) | Scales values from a series. | |
| Multiply(Series, Double) | Scales values from a series. | |
| Subtraction(Double, Series) | Subtracts series from a fixed scalar value. | |
| Subtraction(Series, Series) | Creates a new series by subtracting values from the operands. | |
| Subtraction(Series, Double) | Subtracts a fixed scalar value from a series. | |
| UnaryNegation(Series) | Negates values from a series. |