Package | Description |
---|---|
dev.nm.analysis.root.multivariate | |
dev.nm.analysis.root.univariate | |
tech.nmfin.portfoliooptimization.markowitz |
Modifier and Type | Method and Description |
---|---|
Vector |
NewtonSystemRoot.solve(RealScalarFunction[] f,
Vector guess)
Searches for a root, x such that f(x) = 0.
|
Vector |
NewtonSystemRoot.solve(RealVectorFunction f,
Vector guess)
Searches for a root, x such that f(x) = 0.
|
Modifier and Type | Method and Description |
---|---|
double |
NewtonRoot.solve(UnivariateRealFunction f,
double guess) |
double |
HalleyRoot.solve(UnivariateRealFunction f,
double guess) |
double |
Uniroot.solve(UnivariateRealFunction f,
double lower,
double upper,
double... guess)
Search for a root, x, in the interval [lower, upper] such that f(x) = 0.
|
double |
NewtonRoot.solve(UnivariateRealFunction f,
double lower,
double upper,
double... guess) |
double |
HalleyRoot.solve(UnivariateRealFunction f,
double lower,
double upper,
double... guess) |
double |
BisectionRoot.solve(UnivariateRealFunction f,
double lower,
double upper,
double... guess) |
double |
NewtonRoot.solve(UnivariateRealFunction f,
UnivariateRealFunction df_,
double guess)
Searches for a root, x, in the interval [lower, upper] such
that f(x) = 0.
|
double |
HalleyRoot.solve(UnivariateRealFunction f,
UnivariateRealFunction df,
UnivariateRealFunction d2f,
double guess)
Search for a root, x, in the interval [lower, upper] such that f(x) = 0.
|
Modifier and Type | Method and Description |
---|---|
double |
MarkowitzByQP.getRiskAversionCoefficientForTargetReturn(double r,
double lower,
double upper,
int maxIterations) |
double |
MarkowitzByQP.getRiskAversionCoefficientForTargetVariance(double var,
double lower,
double upper,
int maxIterations) |
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