public class MullerSolver extends AbstractUnivariateSolver
Muller's method applies to both real and complex functions, but here we
restrict ourselves to real functions.
This class differs from MullerSolver
in the way it avoids complex
operations.
Muller's original method would have function evaluation at complex point. Since our f(x) is real, we have to find ways to avoid that. Bracketing condition is one way to go: by requiring bracketing in every iteration, the newly computed approximation is guaranteed to be real.
Normally Muller's method converges quadratically in the vicinity of a zero, however it may be very slow in regions far away from zeros. For example, f(x) = exp(x) - 1, min = -50, max = 100. In such case we use bisection as a safety backup if it performs very poorly.
The formulas here use divided differences directly.
MullerSolver2
Constructor and Description |
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MullerSolver()
Construct a solver with default accuracy (1e-6).
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MullerSolver(double absoluteAccuracy)
Construct a solver.
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MullerSolver(double relativeAccuracy,
double absoluteAccuracy)
Construct a solver.
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getAbsoluteAccuracy, getEvaluations, getFunctionValueAccuracy, getMax, getMaxEvaluations, getMin, getRelativeAccuracy, getStartValue, solve, solve, solve
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
getAbsoluteAccuracy, getEvaluations, getFunctionValueAccuracy, getMaxEvaluations, getRelativeAccuracy, solve, solve, solve
public MullerSolver()
public MullerSolver(double absoluteAccuracy)
absoluteAccuracy
- Absolute accuracy.public MullerSolver(double relativeAccuracy, double absoluteAccuracy)
relativeAccuracy
- Relative accuracy.absoluteAccuracy
- Absolute accuracy.Jas4pp 1.5 © Java Analysis Studio for Particle Physics