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Packages that use Parameters | |
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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 defing a phylogenetic model. |
Optimizers | Provides classes for optimising a likelihood. |
Parameters | Provides classes for defining parameters used in the various calculations. |
Simulations | Provides a class to create simulate data. |
Trees | Provides classes to define a tree and any constraints on that tree. |
Uses of Parameters in Ancestors |
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Methods in Ancestors with parameters of type Parameters | |
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abstract Alignment |
AncestralJoint.calculate(Parameters params)
Calculates the reconstruction |
Alignment |
AncestralJointBB.calculate(Parameters p)
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Alignment |
AncestralJointDP.calculate(Parameters params)
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AncestralMarginal.Result |
AncestralMarginal.calculate(Parameters params)
Calculates the reconstruction |
Uses of Parameters in Likelihood |
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Methods in Likelihood that return Parameters | |
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Parameters |
Likelihood.getParameters()
Gets the parameters used to calculate this likelihood |
Methods in Likelihood with parameters of type Parameters | |
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Likelihood |
Calculator.calculate(Parameters p)
Calculates the likelihood for a given set of parameters |
Constructors in Likelihood with parameters of type Parameters | |
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ConfidenceInterval(Calculator l,
Parameters p)
Default constructor |
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Probabilities(Model m,
Tree t,
Parameters p)
Constructor |
Uses of Parameters in Models |
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Methods in Models with parameters of type Parameters | |
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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(Parameters p,
int num)
Creates a simple BDI 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 Reversable model with gamma-distributed rate across sites |
static Model |
DNAModelFactory.GTR(Parameters p)
Creates an instance of a General Time Reversable 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(Parameters p,
int num)
Creates a simple parsimony-style 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. |
Uses of Parameters in Optimizers |
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Methods in Optimizers with parameters of type Parameters | |
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Likelihood |
GoldenSection.maximise(Calculator l,
Parameters params)
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Likelihood |
NelderMead.maximise(Calculator l,
Parameters params)
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Likelihood |
Optimizer.maximise(Calculator l,
Parameters p)
Maximises the likelihood, logging to screen. |
Likelihood |
GoldenSection.maximise(Calculator l,
Parameters params,
java.io.File log)
|
Likelihood |
NelderMead.maximise(Calculator l,
Parameters params,
java.io.File log)
|
Likelihood |
Optimizer.maximise(Calculator l,
Parameters params,
java.io.File log)
Maximises the likelihood, logging to a file. |
Uses of Parameters in Parameters |
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Methods in Parameters that return Parameters | |
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Parameters |
Parameters.clone()
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static Parameters |
Parameters.fromFile(java.io.File f)
Reads parameters from a file. |
Methods in Parameters with parameters of type Parameters | |
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void |
Parameters.addParameters(Parameters pp)
Adds the parameters from another set of parameters |
Uses of Parameters in Simulations |
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Methods in Simulations with parameters of type Parameters | |
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double |
HypothesisTest.test(Tree t,
Alignment a,
Alignment unobserved,
Parameters nullParams,
Parameters altParams)
Does a hpyothesis 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 hpyothesis test on the given data and gives a p-value |
Constructors in Simulations with parameters of type Parameters | |
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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. |
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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 sattes. |
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Simulate(java.util.Map<java.lang.String,Model> m,
Tree t,
Parameters p,
Alignment unobserved,
java.util.Map<java.lang.String,Constrainer> con)
Creates an object to simulate data for a given set of models, a tree, parameters, unobserved states and constrainers. |
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Simulate(Model m,
Tree t,
Parameters p)
Creates an object to simulate data for a given model, tree and parameters. |
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Simulate(Model m,
Tree t,
Parameters p,
Alignment unobserved)
Creates an object to simulate data for a given model, tree, parameters and unobserved states. |
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Simulate(Model m,
Tree t,
Parameters p,
Alignment unobserved,
Constrainer con)
Creates an object to simulate data for a given model, tree, parameters, unobserved states and constraints. |
Uses of Parameters in Trees |
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Methods in Trees that return Parameters | |
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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 | |
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Tree(Tree old,
Parameters p)
Duplicates a tree topology while replacing branch lengths using the appropiate parameter |
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