Uses of Interface
pal.math.UnivariateFunction
Packages that use UnivariateFunction
Package
Description
Classes for reading and generating distance matrices, including computation
of pairwise distances for sequence data (maximum-likelihood and observed
distances).
Classes for math stuff such as optimisation, numerical derivatives, matrix exponentials,
random numbers, special function etc.
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Uses of UnivariateFunction in pal.distance
Classes in pal.distance that implement UnivariateFunctionModifier and TypeClassDescriptionclasscomputation of the (negative) log-likelihood for a pair of sequences -
Uses of UnivariateFunction in pal.math
Classes in pal.math that implement UnivariateFunctionModifier and TypeClassDescriptionclassconverts a multivariate function into a univariate functionclassconverts a multivariate function into a univariate function by keeping all but one argument constantMethods in pal.math with parameters of type UnivariateFunctionModifier and TypeMethodDescriptiondoubleUnivariateMinimum.findMinimum(double x, UnivariateFunction f) Find minimum (first estimate given)doubleUnivariateMinimum.findMinimum(double x, UnivariateFunction f, int fracDigits) Find minimum (first estimate given, desired number of fractional digits specified)doubleUnivariateMinimum.findMinimum(UnivariateFunction f) Find minimum (no first estimate given)doubleUnivariateMinimum.findMinimum(UnivariateFunction f, int fracDigits) Find minimum (no first estimate given, desired number of fractional digits specified)static doubleNumericalDerivative.firstDerivative(UnivariateFunction f, double x) determine first derivativedoubleUnivariateMinimum.optimize(double x, UnivariateFunction f, double tol) The actual optimization routine (Brent's golden section method)doubleUnivariateMinimum.optimize(double x, UnivariateFunction f, double tol, double lowerBound, double upperBound) The actual optimization routine (Brent's golden section method)doubleUnivariateMinimum.optimize(UnivariateFunction f, double tol) The actual optimization routine (Brent's golden section method)doubleUnivariateMinimum.optimize(UnivariateFunction f, double tol, double lowerBound, double upperBound) The actual optimization routine (Brent's golden section method)static doubleNumericalDerivative.secondDerivative(UnivariateFunction f, double x) determine second derivative