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CsSmooth Class
Extension of the Spline class to construct a smooth cubic spline from noisy data points.
Inheritance Hierarchy

Namespace: Imsl.Math
Assembly: ImslCS (in ImslCS.dll) Version: 6.5.2.0
Syntax
[SerializableAttribute]
public class CsSmooth : Spline

The CsSmooth type exposes the following members.

Constructors
Methods
  NameDescription
Public methodDerivative(Double)
Returns the value of the first derivative of the spline at a point.
(Inherited from Spline.)
Public methodDerivative(Double, Int32)
Returns the value of the derivative of the spline at a point.
(Inherited from Spline.)
Public methodDerivative(Double, Int32)
Returns the value of the derivative of the spline at each point of an array.
(Inherited from Spline.)
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Public methodEval(Double)
Returns the value of the spline at a point.
(Inherited from Spline.)
Public methodEval(Double)
Returns the value of the spline at each point of an array.
(Inherited from Spline.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodGetBreakpoints
Returns a copy of the breakpoints.
(Inherited from Spline.)
Public methodGetHashCode
Serves as a hash function for a particular type.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodIntegral
Returns the value of an integral of the spline.
(Inherited from Spline.)
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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Remarks

Class CsSmooth is designed to produce a C^2 cubic spline approximation to a data set in which the function values are noisy. This spline is called a smoothing spline. It is a natural cubic spline with knots at all the data abscissas x = xData, but it does not interpolate the data (x_i, f_i). The smoothing spline S is the unique C^2 function that minimizes

\int\limits_a^b {S''\left( x \right)^2 dx}

subject to the constraint

\sum\limits_{i = 0}^{n-1} {\left| {{{(S\left( 
            {x_i } \right) - f_i }) {w_i }}} \right|} ^2  \le \sigma

where \sigma is the smoothing parameter. The reader should consult Reinsch (1967) for more information concerning smoothing splines. CsSmooth solves the above problem when the user provides the smoothing parameter \sigma. CsSmoothC2 attempts to find the "optimal" smoothing parameter using the statistical technique known as cross-validation. This means that (in a very rough sense) one chooses the value of \sigma so that the smoothing spline (S_\sigma) best approximates the value of the data at x_I, if it is computed using all the data except the i-th; this is true for all i = 0, \ldots, n-1. For more information on this topic, we refer the reader to Craven and Wahba (1979).

See Also

Reference

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