Smoothing.Lowess Method
Definition
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23
Overload List
Lowess( | Applies a LOWESS filter to the specified signal. |
Lowess( | Applies a LOWESS filter to the specified signal. |
Lowess( | Applies a LOWESS filter to the specified signal. |
Lowess( | Applies a LOWESS filter to the specified signal. |
Lowess(Vector<Double>, Double, Int32, Double)
public static Vector<double> Lowess(
Vector<double> signal,
double smoothingFactor,
int robustSteps = 0,
double delta = 0
)
Parameters
- signal Vector<Double>
- The signal to filter.
- smoothingFactor Double
- The size of the neighbourhood that contributes to the smoothing at each point as a fraction of the total range of the input.
- robustSteps Int32 (Optional)
- (Optional.) The number of robustness iterations. The default is 0.
- delta Double (Optional)
- (Optional.) Distance within which robust regression is not recomputed.
Return Value
Vector<Double>The smoothed signal.
Remarks
When the number of data points is large, the computation time can be reduced by setting delta to a suitable value. After the initial robust regression weights are computed, the full regression is only performed for points that are delta apart. Interpolation is used for any intermediate points.
Exceptions
ArgumentNullException | signal is null. |
ArgumentOutOfRangeException | smoothingFactor is less than or equal to zero or greater than 1. |
Lowess(Vector<Double>, Int32, Int32, Double)
public static Vector<double> Lowess(
Vector<double> signal,
int windowLength,
int robustSteps = 0,
double delta = 0
)
Parameters
- signal Vector<Double>
- The signal to filter.
- windowLength Int32
- The length of the smoothing window.
- robustSteps Int32 (Optional)
- (Optional.) The number of robustness iterations. The default is 0.
- delta Double (Optional)
- (Optional.) Distance within which robust regression is not recomputed.
Return Value
Vector<Double>The smoothed signal.
Remarks
When the number of data points is large, the computation time can be reduced by setting delta to a suitable value. After the initial robust regression weights are computed, the full regression is only performed for points that are delta apart. Interpolation is used for any intermediate points.
Exceptions
ArgumentNullException | signal is null. |
ArgumentOutOfRangeException | windowLength is less than two or greater than the length of signal. -or- windowLength is not odd. |
Lowess(Vector<Double>, Vector<Double>, Double, Int32, Double)
public static Vector<double> Lowess(
Vector<double> x,
Vector<double> signal,
double smoothingFactor,
int robustSteps = 0,
double delta = 0
)
Parameters
- x Vector<Double>
- The x values of the signal.
- signal Vector<Double>
- The signal to filter.
- smoothingFactor Double
- The size of the neighbourhood that contributes to the smoothing at each point as a fraction of the total range of x.
- robustSteps Int32 (Optional)
- (Optional.) The number of robustness iterations. The default is 0.
- delta Double (Optional)
- (Optional.) Distance within which robust regression is not recomputed.
Return Value
Vector<Double>The filtered signal.
Remarks
When the number of data points is large, the computation time can be reduced by setting delta to a suitable value. After the initial robust regression weights are computed, the full regression is only performed for points that are delta apart. Interpolation is used for any intermediate points.
Exceptions
ArgumentNullException | x is null. -or- signal is null. |
Dimension | x and signal do not have the same length. |
ArgumentOutOfRangeException | smoothingFactor is less than or equal to zero or greater than 1. |
Lowess(Vector<Double>, Vector<Double>, Int32, Int32, Double)
public static Vector<double> Lowess(
Vector<double> x,
Vector<double> signal,
int windowLength,
int robustSteps = 0,
double delta = 0
)
Parameters
- x Vector<Double>
- The x values of the signal.
- signal Vector<Double>
- The signal to filter.
- windowLength Int32
- The length of the smoothing window.
- robustSteps Int32 (Optional)
- (Optional.) The number of robustness iterations. The default is 0.
- delta Double (Optional)
- (Optional.) Distance within which robust regression is not recomputed.
Return Value
Vector<Double>The filtered signal.
Remarks
When the number of data points is large, the computation time can be reduced by setting delta to a suitable value. After the initial robust regression weights are computed, the full regression is only performed for points that are delta apart. Interpolation is used for any intermediate points.
Exceptions
ArgumentNullException | x is null. -or- signal is null. |
Dimension | x and signal do not have the same length. |
ArgumentOutOfRangeException | windowLength is less than two or greater than the length of signal. -or- windowLength is not odd. |