Contains methods for computing basic mathematical functions of uncertain values.
Namespace:
Meta.Numerics.StatisticsAssembly: Meta.Numerics (in Meta.Numerics.dll) Version: 1.5.0.0 (1.5.0.0)
Syntax
| C# | Visual Basic | Visual C++ |
public static class UncertainMath
Public NotInheritable Class UncertainMath
public ref class UncertainMath abstract sealed
Members
| All Members | Methods  |
 Public Protected | Instance Static  | Declared Inherited | XNA Framework Only  .NET Compact Framework Only  |
| Member | Description | |
|---|---|---|
| Acos(UncertainValue) |
Computes the arccosine of an uncertain value.
|
| Asin(UncertainValue) |
Computes the arcsine of an uncertain value.
|
| Atan(UncertainValue) |
Computes the arctangent of an uncertain value.
|
| Atan2(UncertainValue, UncertainValue) |
Computes the arctangent of the ratio of two uncertain values.
|
| Cos(UncertainValue) |
Computes the cosine of an uncertain value.
|
| Cosh(UncertainValue) |
Computes the hyperbolic cosine of an uncertain value.
|
| Exp(UncertainValue) |
Computes e to the power of an uncertain value.
|
| Log(UncertainValue) |
Computes the natural logarithm of an uncertain value.
|
| Pow(UncertainValue, Double) |
Computes an uncertain value raised to an arbitrary power.
|
| Sin(UncertainValue) |
Computes the sine of an uncertain value.
|
| Sinh(UncertainValue) |
Computes the hyperbolic sine of an uncertain value.
|
| Sqrt(UncertainValue) |
Computes the square root of an uncertain value.
|
| Tan(UncertainValue) |
Computes the tangent of an uncertain value.
|
| Tanh(UncertainValue) |
Computes the hyperbolic tangent of an uncertain value.
|
Remarks
The methods in this static class perform the same basic mathematical operations as the methods of the Math class, accounting for the uncertainty in the inputs to produce a corresponding uncertainty in the output.
As with operations on uncertain values, the methods assume that the uncertainty in input parameters represents the standard deviation of a distribution of measurements, and produce a value for the uncertainty in the output which represent a corresponding standard deviation, under the assumption that the standard deviations are small relative to the best values.
Inheritance Hierarchy
See Also
