Package | Description |
---|---|
jebl.evolution.coalescent | |
jebl.math |
Modifier and Type | Class | Description |
---|---|---|
class |
Coalescent |
A likelihood function for the coalescent.
|
Modifier and Type | Method | Description |
---|---|---|
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.
|
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 |
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.
|
void |
OrthogonalSearch.optimize(MultivariateFunction f,
double[] xvec,
double tolfx,
double tolx) |
|
void |
OrthogonalSearch.optimize(MultivariateFunction f,
double[] xvec,
double tolfx,
double tolx,
MinimiserMonitor monitor) |
Constructor | Description |
---|---|
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/