pal.eval
Class DemographicValue

java.lang.Object
  pal.eval.DemographicValue

All Implemented Interfaces:

MultivariateFunction

public class DemographicValue

extends java.lang.Object

implements MultivariateFunction

estimates demographic parameters by maximising the coalescent prior for a tree with given branch lengths.

Field Summary

protected CoalescentIntervals	intervals
double	logL Log-Likelihood
protected DemographicModel	model

Constructor Summary

DemographicValue()

Method Summary

double	compute() compute log-likelihood for current model return negative log-likelihood
protected void	computeLogLikelihood()
double	evaluate(double[] params) compute function value
CoalescentIntervals	getCoalescentIntervals() Returns the coalescent tree of this likelihood value.
DemographicModel	getDemographicModel() Returns the demographic model of this likelihood value
double	getLowerBound(int n) get lower bound of argument n
int	getNumArguments() get number of arguments
OrthogonalHints	getOrthogonalHints()
double	getUpperBound(int n) get upper bound of argument n
double	optimize() optimize log-likelihood using default optimizer return minimum negative log-likelihood
double	optimize(MultivariateMinimum givenMvm) optimize log-likelihood value and compute corresponding SEs given an optimizer
void	setCoalescentIntervals(CoalescentIntervals ci) define coalescent tree.
void	setDemographicModel(DemographicModel m) define model

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

logL

public double logL

Log-Likelihood

intervals

protected CoalescentIntervals intervals

model

protected DemographicModel model

Constructor Detail

DemographicValue

public DemographicValue()

Method Detail

setDemographicModel

public void setDemographicModel(DemographicModel m)

define model

Parameters:

m - model of demographic

getDemographicModel

public DemographicModel getDemographicModel()

Returns the demographic model of this likelihood value

getCoalescentIntervals

public CoalescentIntervals getCoalescentIntervals()

Returns the coalescent tree of this likelihood value.

setCoalescentIntervals

public void setCoalescentIntervals(CoalescentIntervals ci)

define coalescent tree.

compute

public double compute()

compute log-likelihood for current model return negative log-likelihood

optimize

public double optimize()

optimize log-likelihood using default optimizer return minimum negative log-likelihood

optimize

public double optimize(MultivariateMinimum givenMvm)

optimize log-likelihood value and compute corresponding SEs given an optimizer

Returns:

minimimum negative log-likelihood value

evaluate

public double evaluate(double[] params)

Description copied from interface: MultivariateFunction

compute function value

Specified by:

evaluate in interface MultivariateFunction

Parameters:

params - function argument (vector)

Returns:

function value

getNumArguments

public int getNumArguments()

Description copied from interface: MultivariateFunction

get number of arguments

Specified by:

getNumArguments in interface MultivariateFunction

Returns:

number of arguments

getLowerBound

public double getLowerBound(int n)

Description copied from interface: MultivariateFunction

get lower bound of argument n

Specified by:

getLowerBound in interface MultivariateFunction

Parameters:

n - argument number

Returns:

lower bound

getUpperBound

public double getUpperBound(int n)

Description copied from interface: MultivariateFunction

get upper bound of argument n

Specified by:

getUpperBound in interface MultivariateFunction

Parameters:

n - argument number

Returns:

upper bound

computeLogLikelihood

protected void computeLogLikelihood()

getOrthogonalHints

public OrthogonalHints getOrthogonalHints()

Specified by:

getOrthogonalHints in interface MultivariateFunction

Returns:

null