Class | Description |
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AnalysisOfVariance |
A class performing an analysis of variance
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AuxDer |
A class computing the derivative f'(x) of f(x) at x = X.
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AuxDri |
A class computing the Matrix A of derivatives needed int classes LsqNon and LsqMar
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AuxGrad |
A class computing the gradient vector of a function of n variables
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AuxHesse |
A class computing the Hessian matrix of second derivatives of a function of n variables
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AuxJInputGroup |
A class representing a JPanel with a border, a border title, and
a tooltip text, to which other elements can be added, one below the other.
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AuxJNumberInput |
A class representing a JPanel carrying a JLabel with Text (and tooltip text)
and a JTextField for numerical input, the validity of which is checked.
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AuxJRButtonGroup |
A class representing a JPanel carrying a vertical row of radio buttons with a border, a border title,
a tooltip text; all buttons are listened to by the same ActionListener.
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AuxZero |
A class with which a zero of a scalar monotonic function of a single variable is found
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DatanFrame |
A class providing a JFrame with input and output possibilities for Datan examples.
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DatanMatrix |
A class representing a matrix.
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DatanRandom |
A class providing methods for computing random numbers
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DatanUserFunction |
An abstract class which has to be extended by the user to yield a class computing a scalar function
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DatanVector |
A class representing a vector.
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FunctionOnLine |
A class computing the value of a function at a given point on straight line in n-dimensional space.
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Gamma |
A class providing methods for computing the Gamma function and related functions
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Histogram |
A class representing a histogram.
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LsqAsg |
A class determining the asymmetric errors
for a set of parameters determined by the least square method for the general case using class LsqGen.
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LsqAsm |
A class determining the asymmetric errors
for a set of parameters determined by the least square method using class LsqMar.
|
LsqAsn |
A class determining the asymmetric errors
for a set of parameters determined by the least square method using class LsqNon.
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LsqGen |
A class performing the least-squares fit of a nonlinear function to a set of data,
using an iterative procedure with step-size reduction.
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LsqLin |
A class porforming the least-squares fit of a linear function to a set of data.
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LsqMar |
A class performing the least-squares fit of a nonlinear function
to a set of data,using Marquardt's method.
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LsqNon |
A class performing the least-squares fit of a nonlinear function to a set of data,
using an iterative procedure with step-size reduction.
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LsqPol |
A class porforming the least-squares fit of a polynomial to a set of data.
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MinAsy |
A class determining the asymmetric errors
for a set of parameters determined by minimization.
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MinCjg |
A class determining the minimum of a function in n-dimensional space by the method of conjugate directions.
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MinCombined |
A class determining the minimum of a function along a straight line in n-dimensional space
according to combination the method of the golden section and of quadratic interpolation
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MinCov |
A class determining the covariance matrix / confidence matrix
for a set of parameters determined by minimization.
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MinDir |
A class determining the minimum of a function along a straight line in n-dimensional space.
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MinEnclose |
A class trying to find an interval along a straight line in n-dimensional space which contains
the minimum on that line of a function in n-space.
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MinGold |
A class determining the minimum of a function along a straight line in n-dimensional space
according to the method of the golden section
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MinMar |
A class determining the minimum of a function in n-dimensional space by Marquardt's method of.
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MinParab |
A class determining the extremum of a parabola through three points (xa,ya), (xb,yb),(xb,yc).
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MinPow |
A class determining the minimum of a function in n-dimensional space by Powell's method of selected directions.
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MinQdr |
A class determining the minimum of a function in n-dimensional space by the method of of the quadratic form.
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MinSim |
A class determining the minimum of a function in n-dimensional space by the simplex method.
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Regression |
A class performing polynomial regression.
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Sample |
A class representing a sample.
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SmallSample |
A class providing methods to compute confidence limits for small samples
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StatFunct |
A class providing methods for computing statistical functions
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TimeSeries |
A class performing time series analysis
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