Uses of Class
Parameters.Parameters

Packages that use Parameters

Package	Description
Ancestors	Provides classed to calculate ancestral reconstruction.
Likelihood	Provides classes for calculating the likelihood of a tree given a model and an alignment.
Models	Provides classes for defining a phylogenetic model.
ModelTest
Optimizers	Provides classes for optimising a likelihood.
Parameters	Provides classes for defining parameters used in the various calculations.
Simulations	Provides a class to create simulated data.
Trees	Provides classes to define a tree.

Uses of Parameters in Ancestors

Methods in Ancestors with parameters of type Parameters

Modifier and Type	Method and Description
abstract Alignment	AncestralJoint.calculate(Parameters params) Calculates the reconstruction
Alignment	AncestralJointBB.calculate(Parameters p)
Alignment	AncestralJointDP.calculate(Parameters params)
AncestralMarginal.Result	AncestralMarginal.calculate(Parameters params) Calculates the reconstruction

Uses of Parameters in Likelihood

Methods in Likelihood that return Parameters

Modifier and Type	Method and Description
Parameters	Likelihood.getParameters() Gets the parameters used to calculate the likelihood

Methods in Likelihood with parameters of type Parameters

Modifier and Type	Method and Description
R	Calculator.calculate(Parameters p) Abstract method for actually calculating the likelihood
abstract SiteLikelihood	Calculator.calculateSite(Site s, Tree t, Parameters p, Probabilities tp, java.util.Map<java.lang.String,SiteLikelihood.NodeLikelihood> nl) Calculate the likelihood for a single site.
SiteLikelihood	StandardCalculator.calculateSite(Site s, Tree t, Parameters p, Probabilities tp, java.util.Map<java.lang.String,SiteLikelihood.NodeLikelihood> nl)
abstract R	Calculator.combineSites(java.util.Map<Site,SiteLikelihood> sites, Parameters p) Combines the likelihood from each site into a alignment likelihood
StandardLikelihood	StandardCalculator.combineSites(java.util.Map<Site,SiteLikelihood> sites, Parameters p)
protected java.util.Map<Site,SiteLikelihood>	Calculator.siteCalculate(Parameters p) Calculates the likelihood for each site

Constructors in Likelihood with parameters of type Parameters

Constructor and Description
Calculator.SiteCalculator(Site s, Tree t, Parameters p, Probabilities tp, java.util.Map<java.lang.String,SiteLikelihood.NodeLikelihood> nl) Standard constructor
ConfidenceInterval(StandardCalculator l, Parameters p) Default constructor
Likelihood(double likelihood, Parameters p) Creates a simple likelihood result
Probabilities(Model m, Tree t, Parameters p) Constructor

Uses of Parameters in Models

Methods in Models that return Parameters

Modifier and Type	Method and Description
Parameters	DNAModelFactory.getParameters() Gets the parameters for the relevant model

Methods in Models with parameters of type Parameters

Modifier and Type	Method and Description
static Model	DuplicationModelFactory.BD_NoZero_Gamma(Parameters p, int num, int numCats) Creates a Birth Death model with no zero state and gamma distributed rates-across sites.
static Model	DuplicationModelFactory.BD_NoZero_Gamma(Parameters p, int num, int numCats, boolean fixed) Creates a Birth Death model with no zero state and gamma distributed rates-across sites.
static Model	DuplicationModelFactory.BD_NoZero(Parameters p, int num) Creates a Birth Death model with no zero state.
static Model	DuplicationModelFactory.BD_NoZero(Parameters p, int num, boolean fixed) Creates a Birth Death model with no zero state.
static Model	DuplicationModelFactory.BDI_Gamma(Parameters p, int num, int numCats) Creates a simple BDI model with gamma-distributed rate across sites.
static Model	DuplicationModelFactory.BDI_Gamma(Parameters p, int num, int numCats, boolean fixed) Creates a simple BDI model with gamma-distributed rate across sites
static Model	DuplicationModelFactory.BDI(Parameters p, int num) Creates a simple BDI model.
static Model	DuplicationModelFactory.BDI(Parameters p, int num, boolean fixed) Creates a simple BDI model
static Model	DuplicationModelFactory.BDIE_Gamma(Parameters p, int num, int numCats) Creates a simple BDI model with gamma-distributed rate across sites.
static Model	DuplicationModelFactory.BDIE_Gamma(Parameters p, int num, int numCats, boolean fixed) Creates a simple BDIE model with gamma-distributed rate across sites
static Model	DuplicationModelFactory.BDIE(Parameters p, int num, boolean fixed) Creates a simple BDIE model
static Model	DNAModelFactory.Felsenstein81_Gamma(Parameters p, int numCats) Creates an instance of a JFelsenstein 81 model with gamma-distributed rate across sites
static Model	DNAModelFactory.Felsenstein81(Parameters p) Creates an instance of a Felsenstein 81 model
static Model	DNAModelFactory.GTR_Gamma(Parameters p, int numCats) Creates an instance of a General Time Reversible model with gamma-distributed rate across sites
static Model	DNAModelFactory.GTR(Parameters p) Creates an instance of a General Time Reversible model
static Model	DNAModelFactory.HKY_Gamma(Parameters p, int numCats) Creates an instance of a HKY model with gamma-distributed rate across sites
static Model	DNAModelFactory.HKY(Parameters p) Creates an instance of a HKY model
static Model	DNAModelFactory.JukesCantor_Gamma(Parameters p, int numCats) Creates an instance of a Jukes-Cantor model with gamma-distributed rate across sites
static Model	DNAModelFactory.JukesCantor(Parameters p) Creates an instance of a Jukes-Cantor model
static Model	DNAModelFactory.Kimura_Gamma(Parameters p, int numCats) Creates an instance of a Kimura 2-parameter model with gamma-distributed rate across sites
static Model	DNAModelFactory.Kimura(Parameters p) Creates an instance of a Kimura 2-paramter model
static Model	DuplicationModelFactory.Parsimony_Gamma(Parameters p, int num, int numCats) Creates a simple parsimony-style model with gamma-distributed rate across sites.
static Model	DuplicationModelFactory.Parsimony_Gamma(Parameters p, int num, int numCats, boolean fixed) Creates a simple parsimony-style model with gamma-distributed rate across sites
static Model	DuplicationModelFactory.Parsimony(Parameters p, int num) Creates a simple parsimony-style model
static Model	DuplicationModelFactory.Parsimony(Parameters p, int num, boolean fixed) Creates a simple parsimony-style model
static Model	RYModelFactory.RY_Gamma(Parameters p, int numCats) Creates an instance of a RY model with gamma-distributed rate across sites
static Model	RYModelFactory.RY(Parameters p) Creates an instance of a RY model
void	Model.setParameters(Parameters p) Sets the parameters of a model to the values contained in the Parameters data structure.
void	RateCategory.setParameters(Parameters p) Updates the parameters in the RateCategory and recalculates matrices / frequencies if necessary.

Uses of Parameters in ModelTest

Methods in ModelTest that return Parameters

Modifier and Type	Method and Description
Parameters	TestInstance.getParameters() Get the parameters associated with this instance

Methods in ModelTest with parameters of type Parameters

Modifier and Type	Method and Description
double	HypothesisTest.test(java.util.Map<java.lang.String,Tree> t, Alignment a, Alignment unobserved, Parameters nullParams, Parameters altParams) Does a hypothesis test on the given data and gives a p-value
double	HypothesisTest.test(java.util.Map<java.lang.String,Tree> t, Alignment a, Alignment unobserved, Parameters nullParams, Parameters altParams, java.util.Map<java.lang.String,java.lang.String> recode) Does a hypothesis test on the given data and gives a p-value
double	HypothesisTest.test(Tree t, Alignment a, Alignment unobserved, Parameters nullParams, Parameters altParams) Does a hypothesis test on the given data and gives a p-value
double	HypothesisTest.test(Tree t, Alignment a, Alignment unobserved, Parameters nullParams, Parameters altParams, java.util.Map<java.lang.String,java.lang.String> recode) Does a hypothesis test on the given data and gives a p-value

Constructors in ModelTest with parameters of type Parameters

Constructor and Description
TestInstance(Calculator<Likelihood> c, Parameters p) Creates an instance
TestInstance(Calculator<Likelihood> c, Parameters p, Adapter adapter, Alignment distinct) Creates a named instance.
TestInstance(Calculator<Likelihood> c, Parameters p, java.lang.String name) Creates a named instance.
TestInstance(Calculator<Likelihood> c, Parameters p, java.lang.String name, Adapter adapter, Alignment distinct) Creates a named instance.

Uses of Parameters in Optimizers

Methods in Optimizers with parameters of type Parameters

Modifier and Type	Method and Description
R	Optimizable.calculate(Parameters p) The optimisable likelihood function.
<R extends Likelihood> R	ConjugateGradient.maximise(Optimizable<R> c, Parameters p)
<R extends Likelihood> R	GoldenSection.maximise(Optimizable<R> l, Parameters params)
<R extends Likelihood> R	NelderMead.maximise(Optimizable<R> l, Parameters params)
<R extends Likelihood> R	Optimizer.maximise(Optimizable<R> l, Parameters p) Maximises the likelihood, logging to screen.
<R extends Likelihood> R	ConjugateGradient.maximise(Optimizable<R> c, Parameters p, java.io.File log)
<R extends Likelihood> R	GoldenSection.maximise(Optimizable<R> l, Parameters params, java.io.File log)
<R extends Likelihood> R	NelderMead.maximise(Optimizable<R> l, Parameters params, java.io.File log)
<R extends Likelihood> R	Optimizer.maximise(Optimizable<R> l, Parameters params, java.io.File log) Maximises the likelihood, logging to a file.

Uses of Parameters in Parameters

Methods in Parameters that return Parameters

Modifier and Type	Method and Description
Parameters	Parameters.clone()
static Parameters	Parameters.fromFile(java.io.File f) Reads parameters from a file.

Methods in Parameters with parameters of type Parameters

Modifier and Type	Method and Description
void	Parameters.addParameters(Parameters pp) Adds the parameters from another set of parameters

Uses of Parameters in Simulations

Constructors in Simulations with parameters of type Parameters

Constructor and Description
Simulate(java.util.Map<java.lang.String,Model> m, java.util.Map<java.lang.String,Tree> t, Parameters p) Creates an object to simulate data for a given set of models and trees, parameters and unobserved states.
Simulate(java.util.Map<java.lang.String,Model> m, java.util.Map<java.lang.String,Tree> t, Parameters p, Alignment unobserved) Creates an object to simulate data for a given set of models and trees, parameters and unobserved states.
Simulate(java.util.Map<java.lang.String,Model> m, Tree t, Parameters p) Creates an object to simulate data for a given set of models, a tree and parameters.
Simulate(java.util.Map<java.lang.String,Model> m, Tree t, Parameters p, Alignment unobserved) Creates an object to simulate data for a given set of models, a tree, parameters and unobserved states.
Simulate(Model m, java.util.Map<java.lang.String,Tree> t, Parameters p) Creates an object to simulate data for a given model, set of trees, parameters and unobserved states.
Simulate(Model m, java.util.Map<java.lang.String,Tree> t, Parameters p, Alignment unobserved) Creates an object to simulate data for a given model, set of trees, parameters and unobserved states.
Simulate(Model m, Tree t, Parameters p) Creates an object to simulate data for a given model, tree and parameters.
Simulate(Model m, Tree t, Parameters p, Alignment unobserved) Creates an object to simulate data for a given model, tree, parameters and unobserved states.

Uses of Parameters in Trees

Methods in Trees that return Parameters

Modifier and Type	Method and Description
Parameters	Tree.getParameters() Returns a Parameters object containing a parameter for each branch length.
Parameters	Tree.getParametersForEstimation() Returns a Parameters object containing a parameter for each branch length.

Constructors in Trees with parameters of type Parameters

Constructor and Description
Tree(Tree old, Parameters p) Duplicates a tree topology while replacing branch lengths using the appropriate parameter