Package | Description |
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jebl.evolution.coalescent | |
jebl.math |
Modifier and Type | Class and Description |
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class |
Coalescent
A likelihood function for the coalescent.
|
Modifier and Type | Method and Description |
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static double[] |
NumericalDerivative.diagonalHessian(MultivariateFunction f,
double[] x)
determine diagonal of Hessian
|
double |
MultivariateMinimum.findMinimum(MultivariateFunction f,
double[] xvec)
Find minimum close to vector x
|
double |
MultivariateMinimum.findMinimum(MultivariateFunction f,
double[] xvec,
int fxFracDigits,
int xFracDigits)
Find minimum close to vector x
(desired fractional digits for each parameter is specified)
|
double |
MultivariateMinimum.findMinimum(MultivariateFunction f,
double[] xvec,
int fxFracDigits,
int xFracDigits,
MinimiserMonitor monitor)
Find minimum close to vector x
(desired fractional digits for each parameter is specified)
|
static double[] |
NumericalDerivative.gradient(MultivariateFunction f,
double[] x)
determine gradient
|
static void |
NumericalDerivative.gradient(MultivariateFunction f,
double[] x,
double[] grad)
determine gradient
|
void |
MinimiserMonitor.newMinimum(double value,
double[] parameterValues,
MultivariateFunction beingOptimized)
Inform monitor of a new minimum, along with the current arguments.
|
void |
OrthogonalSearch.optimize(MultivariateFunction f,
double[] xvec,
double tolfx,
double tolx) |
abstract void |
MultivariateMinimum.optimize(MultivariateFunction f,
double[] xvec,
double tolfx,
double tolx)
The actual optimization routine
(needs to be implemented in a subclass of MultivariateMinimum).
|
void |
OrthogonalSearch.optimize(MultivariateFunction f,
double[] xvec,
double tolfx,
double tolx,
MinimiserMonitor monitor) |
void |
MultivariateMinimum.optimize(MultivariateFunction f,
double[] xvec,
double tolfx,
double tolx,
MinimiserMonitor monitor)
The actual optimization routine
It finds a minimum close to vector x when the
absolute tolerance for each parameter is specified.
|
Constructor and Description |
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OrthogonalLineFunction(MultivariateFunction func)
construct univariate function from multivariate function
|
OrthogonalLineFunction(MultivariateFunction func,
int selectedDimension,
double[] initialArguments)
construct univariate function from multivariate function
|
http://code.google.com/p/jebl2/