public class Series<T> : ISafeIndexed
where T : struct, new(), IComparable<T>
| SeriesT | Creates a named series. |
| Args | Gets the list of arguments from the series. |
| Count | Gets the number of points in the series. |
| EnumValues | Gets the list of values from the series. |
| First | Gets the first point in the series. |
| ItemIndex | Gets a point given its index. |
| ItemInt32 | Gets a point given its index. |
| ItemRange | Extracts a slice from the series. |
| Kurtosis | Gets the unbiased population kurtosis. |
| Last | Gets the last point in the series. |
| Maximum | Returns the maximum value from the series. |
| Mean | Gets the mean value from the series. |
| Minimum | Returns the minimum value from the series. |
| Name | Gets the name of the series. |
| Points | Gets the sorted list of points. |
| PopulationKurtosis | Gets the kurtosis from the full population. |
| PopulationSkewness | Get the skewness from the full population. |
| PopulationStandardDeviation | Gets the standard deviation from the full population. |
| PopulationVariance | Gets the variance from the full population. |
| Skewness | Gets the unbiased population skewness. |
| StandardDeviation | Gets the unbiased standard deviation. |
| Stats | Gets statistics on the series. |
| Ticker | Gets the ticker of the series. |
| Type | Is this a raw (Prices) series or a derived one? |
| Values | Gets the values array as a vector. |
| Variance | Gets the unbiased variance. |
| AbsMax | Gets the maximum absolute value. |
| AbsMin | Gets the minimum absolute value. |
| ACF | Computes autocorrelation for all lags. |
| 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. |
| AutoRegression | Finds the coefficients for an autoregressive model. |
| Combine | Calculates the weighted sum of an array of series. |
| Contains | Checks if the series contains the given value. |
| Correlation | Computes the Pearson correlation between two series. |
| CorrelationMatrix | Computes the correlation matrix for a group of series. |
| Correlogram | Computes autocorrelation for a range of lags. |
| Covariance | Computes the covariance between two series. |
| CovarianceMatrix | Computes the covariance matrix for a group of series. |
| Create | Creates a series with integer arguments given its values. |
| Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) |
| Fft | Computes the real discrete Fourier transform. |
| GetHashCode | Serves as the default hash function. (Inherited from Object) |
| GetSliceStats | Gets statistics on a slice of the series. |
| GetType | Gets the Type of the current instance. (Inherited from Object) |
| IndexOf | Returns the zero-based index of the first occurrence of a value. |
| LinearModel | Multilinear regression based in Ordinary Least Squares. |
| MovingAverage | Finds the coefficients for a moving average model. |
| NCdf | The normal cumulative distribution function of the most recent value. |
| NCdf(Double) | The normal cumulative distribution function. |
| PACF | Computes the partial autocorrelation for all lags. |
| Percentiles | Returns ascendenly sorted values. |
| SafeThis | Safe access to the series' points. If the index is out of range, a zero is returned. |
| Slice | Takes a slice from a series. |
| Sum | Calculates the sum of the series values. |
| ToString | Gets a textual representation of the series. (Overrides ObjectToString) |
| Addition(SeriesT, SeriesT) | Creates a new series by adding values from the operands. |
| Multiply(Double, SeriesT) | Scales values from a series. |
| Multiply(SeriesT, Double) | Scales values from a series. |
| Subtraction(SeriesT, SeriesT) | Creates a new series by subtracting values from the operands. |