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Packages that use SubstitutionModel | |
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pal.distance | Classes for reading and generating distance matrices, including computation of pairwise distances for sequence data (maximum-likelihood and observed distances). |
pal.eval | Classes for evaluating evolutionary hypothesis (chi-square and likelihood criteria) and estimating model parameters. |
pal.statistics | Classes with useful for statistics (normal distribution, Gamma distribution, chi-square distribution, exponential distribution, likelihood-ratio test, chi-square test, descriptive statistics, bootstrap estimators etc.) |
pal.substmodel | Classes describing substitution models, i.e. |
pal.supgma | |
pal.tree | Classes for providing the data structure of trees, for constructing and modifying trees, and for parameterizing trees (e.g., clock constraint). |
pal.treesearch |
Uses of SubstitutionModel in pal.distance |
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Methods in pal.distance with parameters of type SubstitutionModel | |
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static DistanceMatrix |
DistanceTool.constructEvolutionaryDistances(Alignment a,
SubstitutionModel sm)
Construct a distance matrix object such that the distance between sequence A, and sequence B, is the evolutionary distance by a given substitution model. |
static DistanceMatrixGenerator |
DistanceMatrixGenerator.Utils.createEvolutionary(Alignment a,
SubstitutionModel sm)
|
static DistanceMatrixAccess |
DistanceMatrixAccess.Utils.createEvolutionary(Alignment a,
SubstitutionModel sm)
|
static DistanceMatrixGenerator |
DistanceMatrixGenerator.Utils.createParametric(Tree baseTree,
SubstitutionModel sm,
int numberOfSites)
Silly idea stuff |
void |
AlignmentDistanceMatrix.recompute(SitePattern sp,
SubstitutionModel model)
recompute maximum-likelihood distances under new site pattern |
void |
AlignmentDistanceMatrix.recompute(SitePattern sp,
SubstitutionModel model,
AlgorithmCallback callback)
recompute maximum-likelihood distances under new site pattern |
void |
SequencePairLikelihood.updateModel(SubstitutionModel m)
update model of substitution |
void |
PairwiseDistance.updateModel(SubstitutionModel m)
update model of substitution |
Constructors in pal.distance with parameters of type SubstitutionModel | |
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AlignmentDistanceMatrix(SitePattern sp,
SubstitutionModel m)
compute maximum-likelihood distances |
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AlignmentDistanceMatrix(SitePattern sp,
SubstitutionModel m,
AlgorithmCallback callback)
compute maximum-likelihood distances |
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PairwiseDistance(SitePattern sp,
SubstitutionModel m)
Constructor 2 (uses evolutionary model) |
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SequencePairLikelihood(SitePattern sp,
SubstitutionModel m)
initialisation |
Uses of SubstitutionModel in pal.eval |
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Methods in pal.eval that return SubstitutionModel | |
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SubstitutionModel |
LikelihoodValue.getModel()
Returns the model of this likelihood value. |
SubstitutionModel |
SiteDetails.getRelatedModel()
|
Methods in pal.eval with parameters of type SubstitutionModel | |
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protected abstract void |
LHCalculator.AbstractExternal.calculateCategoryPatternProbabilities(double distance,
SubstitutionModel model,
PatternInfo centerPattern,
ConditionalProbabilityStore leftFlatConditionalProbabilities,
ConditionalProbabilityStore rightFlatConditionalProbabilities,
ConditionalProbabilityStore tempStore,
double[][] categoryPatternLogLikelihoodStore)
|
protected abstract void |
LHCalculator.AbstractExternal.calculateCategoryPatternProbabilities(SubstitutionModel model,
PatternInfo centerPattern,
ConditionalProbabilityStore leftConditionalProbabilities,
ConditionalProbabilityStore rightConditionalProbabilities,
double[][] categoryPatternLikelihoodStore)
|
ConditionalProbabilityStore |
LHCalculator.Internal.calculateExtended(double distance,
SubstitutionModel model,
PatternInfo centerPattern,
ConditionalProbabilityStore leftConditionalProbabilities,
ConditionalProbabilityStore rightConditionalProbabilities,
boolean modelChangedSinceLastCall)
|
void |
LHCalculator.External.calculateExtended(double distance,
SubstitutionModel model,
PatternInfo centerPattern,
ConditionalProbabilityStore leftConditionalProbabilities,
ConditionalProbabilityStore rightConditionalProbabilities,
ConditionalProbabilityStore resultStore)
|
double |
LHCalculator.External.calculateLogLikelihood(double distance,
SubstitutionModel model,
PatternInfo centerPattern,
ConditionalProbabilityStore leftFlatConditionalProbabilities,
ConditionalProbabilityStore rightFlatConditionalProbabilities,
ConditionalProbabilityStore tempStore)
Calculate the likelihood given two sub trees (left, right) and their flat (unextend) likeihood probabilities |
double |
LHCalculator.External.calculateLogLikelihood(SubstitutionModel model,
PatternInfo centerPattern,
ConditionalProbabilityStore leftConditionalProbabilities,
ConditionalProbabilityStore rightConditionalProbabilities)
Calculate the likelihood given two sub trees (left, right) and their extended likeihood probabilities |
static double |
LikelihoodTool.calculateLogLikelihood(Tree tree,
Alignment alignment,
SubstitutionModel model)
Calculate the log likelihood of a particular set of phylogenetic data |
double |
LHCalculator.External.calculateLogLikelihoodSingle(SubstitutionModel model,
int[] patternWeights,
int numberOfPatterns,
ConditionalProbabilityStore conditionalProbabilityStore)
Calculate the likelihood given the conditional probabilites at the root |
ConditionalProbabilityStore |
LHCalculator.Internal.calculatePostExtendedFlat(double distance,
SubstitutionModel model,
PatternInfo centerPattern,
ConditionalProbabilityStore leftConditionalProbabilities,
ConditionalProbabilityStore rightConditionalProbabilities,
boolean modelChangedSinceLastCall)
|
void |
LHCalculator.External.calculateSingleExtendedDirect(double distance,
SubstitutionModel model,
int numberOfPatterns,
ConditionalProbabilityStore conditionalProbabilities)
Extend the conditionals back in time by some distance, with some model |
void |
LHCalculator.External.calculateSingleExtendedIndirect(double distance,
SubstitutionModel model,
int numberOfPatterns,
ConditionalProbabilityStore baseConditionalProbabilities,
ConditionalProbabilityStore resultConditionalProbabilities)
Extend the conditionals back in time by some distance, with some model |
SiteDetails |
LHCalculator.External.calculateSiteDetailsRooted(SubstitutionModel model,
PatternInfo centerPattern,
ConditionalProbabilityStore leftConditionalProbabilitiesStore,
ConditionalProbabilityStore rightConditionalProbabilitiesStore)
Calculate the conditional probabilities of each pattern for each category |
SiteDetails |
LHCalculator.AbstractExternal.calculateSiteDetailsRooted(SubstitutionModel model,
PatternInfo centerPattern,
ConditionalProbabilityStore leftConditionalProbabilitiesStore,
ConditionalProbabilityStore rightConditionalProbabilitiesStore)
|
SiteDetails |
LHCalculator.External.calculateSiteDetailsUnrooted(double distance,
SubstitutionModel model,
PatternInfo centerPattern,
ConditionalProbabilityStore leftConditionalProbabilitiesStore,
ConditionalProbabilityStore rightConditionalProbabilitiesStore,
ConditionalProbabilityStore tempStore)
Calculate the conditional probabilities of each pattern for each category |
SiteDetails |
LHCalculator.AbstractExternal.calculateSiteDetailsUnrooted(double distance,
SubstitutionModel model,
PatternInfo centerPattern,
ConditionalProbabilityStore leftFlatConditionalProbabilities,
ConditionalProbabilityStore rightFlatConditionalProbabilities,
ConditionalProbabilityStore tempStore)
|
static SiteDetails |
SiteDetails.Utils.create(double[][] categoryPatternConditionalProbabilities,
boolean isLoggedConditionals,
SubstitutionModel model,
int numberOfPatterns,
int[] sitePatternMatchup,
int numberOfSites,
double[] siteLikelihoods)
Create a Postriors object |
static MolecularClockLikelihoodModel.Instance |
SimpleMolecularClockLikelihoodModel.createInstance(LHCalculator.Factory baseFactory,
SubstitutionModel model)
|
static UnconstrainedLikelihoodModel.Instance |
SimpleUnconstrainedLikelihoodModel.createInstance(LHCalculator.Factory base,
SubstitutionModel model)
Create a SimpleUnconstrainedLikelihoodModel instance |
static UnconstrainedLikelihoodModel.Instance |
SimpleUnconstrainedLikelihoodModel.createInstance(LHCalculator.Generator base,
SubstitutionModel model)
Create a SimpleUnconstrainedLikelihoodModel instance |
static MolecularClockLikelihoodModel.Instance |
SimpleMolecularClockLikelihoodModel.createInstance(SubstitutionModel model)
|
ConditionalProbabilityStore |
LHCalculator.Leaf.getExtendedConditionalProbabilities(double distance,
SubstitutionModel model,
boolean modelChanged)
|
ConditionalProbabilityStore |
SimpleLeafCalculator.getExtendedConditionalProbabilities(double distance,
SubstitutionModel model,
boolean modelChanged)
|
static Alignment |
LikelihoodTool.getMatchingDataType(Alignment alignment,
SubstitutionModel model)
Creates a new alignment that has a compatible data type with a substution model (needed for likelihood stuff) |
static double |
LikelihoodOptimiser.optimiseAlternate(ParameterizedTree tree,
Alignment alignment,
SubstitutionModel model,
MultivariateMinimum minimiser,
int fxFracDigits,
int xFracDigits)
Optimise parameters to acheive maximum likelihood using an alternating stategy. |
static double |
LikelihoodOptimiser.optimiseAlternate(ParameterizedTree tree,
Alignment alignment,
SubstitutionModel model,
MultivariateMinimum minimiser,
int fxFracDigits,
int xFracDigits,
MinimiserMonitor monitor)
Optimise parameters to acheive maximum likelihood using an alternating stategy. |
static Tree |
LikelihoodTool.optimiseClockConstrained(Tree tree,
Alignment alignment,
SubstitutionModel model,
boolean optimiseModel)
Optimise the branches of a tree with regard to maximum likelihood, with a molecular clock assumption, that is, constrained such that all tips are contemporaneous, the tree is treated as rooted. |
static double |
LikelihoodOptimiser.optimiseCombined(ParameterizedTree tree,
Alignment alignment,
SubstitutionModel model,
MultivariateMinimum minimiser,
int fxFracDigits,
int xFracDigits)
Optimise parameters to acheive maximum likelihood using a combined stategy. |
static double |
LikelihoodOptimiser.optimiseCombined(ParameterizedTree tree,
Alignment alignment,
SubstitutionModel model,
MultivariateMinimum minimiser,
int fxFracDigits,
int xFracDigits,
MinimiserMonitor monitor)
Optimise parameters to acheive maximum likelihood using a combined stategy. |
static double |
LikelihoodOptimiser.optimiseModel(Tree tree,
Alignment alignment,
SubstitutionModel model,
MultivariateMinimum minimiser,
int fxFracDigits,
int xFracDigits,
MinimiserMonitor monitor)
Optimise model parameters only to acheive maximum likelihood using a combined stategy. |
static Tree |
LikelihoodTool.optimiseMRDT(Tree tree,
Alignment alignment,
SubstitutionModel model,
TimeOrderCharacterData tocd,
boolean optimiseModel,
double[] rateStore)
Optimise the branches of a tree with regard to maximum likelihood, with under an assumption of a molecular clock with serially sampled data and multiple mutation rate parameters, mu - one for each sampling interval. |
static Tree |
LikelihoodTool.optimiseMRDT(Tree tree,
Alignment alignment,
SubstitutionModel model,
TimeOrderCharacterData tocd,
boolean optimiseModel,
double[] rateChangeTimes,
double[] rateStore)
Optimise the branches of a tree with regard to maximum likelihood, with under an assumption of a molecular clock with serially sampled data and multiple mutation rate parameters, mu, over general time intervals. |
static Tree |
LikelihoodTool.optimiseSRDT(Tree tree,
Alignment alignment,
SubstitutionModel model,
TimeOrderCharacterData tocd,
boolean optimiseModel,
double[] rateStore)
Optimise the branches of a tree with regard to maximum likelihood, with under an assumption of a molecular clock with serially sampled data and a single mutation rate parameter. |
static double |
LikelihoodOptimiser.optimiseTree(ParameterizedTree tree,
Alignment alignment,
SubstitutionModel model,
MultivariateMinimum minimiser,
int fxFracDigits,
int xFracDigits)
Optimise tree branchlengths only to acheive maximum likelihood using a combined stategy. |
static double |
LikelihoodOptimiser.optimiseTree(ParameterizedTree tree,
Alignment alignment,
SubstitutionModel model,
MultivariateMinimum minimiser,
int fxFracDigits,
int xFracDigits,
MinimiserMonitor monitor)
Optimise tree branchlengths only to acheive maximum likelihood using a combined stategy. |
static Tree |
LikelihoodTool.optimiseUnrooted(Tree tree,
Alignment alignment,
SubstitutionModel model,
boolean optimiseModel)
Optimise the branches of a tree with regard to maximum likelihood, with no constraints on the branchlengths (as for an unrooted tree). |
void |
LikelihoodValue.setModel(SubstitutionModel m)
define model (a site pattern must have been set before calling this method) |
void |
GeneralLikelihoodCalculator.setup(Tree t,
SubstitutionModel model)
|
Constructors in pal.eval with parameters of type SubstitutionModel | |
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GeneralLikelihoodCalculator(Alignment baseAlignment,
Tree tree,
SubstitutionModel model)
Constructor taking site pattern, tree and a general substitution model. |
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LikelihoodOptimiser(Tree tree,
Alignment alignment,
SubstitutionModel model)
|
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ModelParameters(SitePattern sp,
SubstitutionModel m)
Constructor |
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SimpleUnconstrainedLikelihoodModel.InternalImpl(LHCalculator.Internal base,
SubstitutionModel model)
|
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SimpleUnconstrainedLikelihoodModel.LeafImpl(LHCalculator.Leaf base,
SubstitutionModel model)
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Uses of SubstitutionModel in pal.statistics |
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Methods in pal.statistics with parameters of type SubstitutionModel | |
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static ReplicateLikelihoodEvaluator |
ReplicateLikelihoodEvaluator.Utils.createRELLEvaluator(SubstitutionModel model)
Create a ReplicateLikelihoodEvaluator that based likelihood on original tree (does no optimisation) |
static LikelihoodEvaluator |
LikelihoodEvaluator.Utils.createSimpleEvaluator(SubstitutionModel model)
Create a simple evaluator that uses UnrootedTreeSearch |
Uses of SubstitutionModel in pal.substmodel |
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Classes in pal.substmodel that implement SubstitutionModel | |
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class |
GeneralRateDistributionSubstitutionModel
|
class |
SingleClassSubstitutionModel
|
static class |
YangCodonModel.SimpleNeutralSelection
A Substitution Model which can be used to implment the Neutral Model (with out continuous rate stuff) Codon model of [1] which uses the weighted sum of trwo base YangCodon models where omega=0, omega=1 repectively [1] Nielsen, R., Yang Z., 1998 Likelihood Models for Detecting Positively Selected Amino Acid Sites and Applications to the HIV-1 Envelope Gene. |
static class |
YangCodonModel.SimplePositiveSelection
A Substitution Model which can be used to implment the Postitive Selection (with out continuous rate stuff) Codon model of [1] which uses the weighted sum of a three base Codon model where omega=0, omega=1 and omega=free [1] Nielsen, R., Yang Z., 1998 Likelihood Models for Detecting Positively Selected Amino Acid Sites and Applications to the HIV-1 Envelope Gene. |
Fields in pal.substmodel declared as SubstitutionModel | |
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static SubstitutionModel |
F81.JC69_MODEL
|
Methods in pal.substmodel that return SubstitutionModel | |
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static SubstitutionModel |
SubstitutionTool.createF81Model(double[] baseFrequencies)
Create an F81 model of substitution |
static SubstitutionModel |
SubstitutionTool.createF84Model(double expectedTsTv,
double[] baseFrequencies)
Create an F84 model of substitution |
static SubstitutionModel |
SubstitutionTool.createGTRModel(double a,
double b,
double c,
double d,
double e,
double[] baseFrequencies)
Create an GTR model of substitution |
static SubstitutionModel |
SubstitutionTool.createJC69Model()
Create a Jukes-cantor model of substitution |
static SubstitutionModel |
SubstitutionTool.createM0YangCodonModel(double kappa,
double omega,
double[] baseFrequencies)
Create an base Yang Codon model (M0) of substitution |
static SubstitutionModel |
SubstitutionTool.createM1YangCodonModel(double kappa,
double p0,
double[] baseFrequencies)
Create an neutral Yang Codon model (M1) of substitution |
static SubstitutionModel |
SubstitutionTool.createM2YangCodonModel(double kappa,
double p0,
double p1,
double omega,
double[] baseFrequencies)
Create an Positive Yang Codon model (M2) of substitution |
static SubstitutionModel |
SubstitutionModel.Utils.createSubstitutionModel(NeoRateMatrix rm,
DataType dt,
double[] equilibriumFrequencies)
|
static SubstitutionModel |
SubstitutionModel.Utils.createSubstitutionModel(RateMatrix rm)
|
static SubstitutionModel |
SubstitutionModel.Utils.createSubstitutionModel(RateMatrix rm,
RateDistribution rd)
|
static SubstitutionModel |
SubstitutionModel.Utils.createSubstitutionModel(RateMatrix rm,
RateDistribution rd,
boolean parameteriseDistribution)
|
static SubstitutionModel |
SubstitutionTool.createTNModel(double kappa,
double r,
double[] baseFrequencies)
Create an Tamura-Nei model of substitution |
SubstitutionModel |
SingleClassSubstitutionModel.getCopy()
|
SubstitutionModel |
YangCodonModel.SimplePositiveSelection.getCopy()
|
SubstitutionModel |
YangCodonModel.SimpleNeutralSelection.getCopy()
|
SubstitutionModel |
GeneralRateDistributionSubstitutionModel.getCopy()
|
Methods in pal.substmodel with parameters of type SubstitutionModel | |
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static double[][][] |
SubstitutionModel.Utils.generateTransitionProbabilityTables(SubstitutionModel model)
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Constructors in pal.substmodel with parameters of type SubstitutionModel | |
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SequenceSimulator(SubstitutionModel model,
int sequenceLength,
boolean stochasticDistribution)
A constructor (with no provided random number generator - a fresh one is created) |
|
SequenceSimulator(SubstitutionModel model,
int sequenceLength,
MersenneTwisterFast random,
boolean stochasticDistribution)
A constructor (with no provided random number generator - a fresh one is created) |
Uses of SubstitutionModel in pal.supgma |
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Methods in pal.supgma with parameters of type SubstitutionModel | |
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SUPGMABase.CISummary |
SUPGMABase.PopulationParameters.inferCI(AlgorithmCallback callback,
int numberOfReplicates,
SimulatedAlignment.Factory alignmentFactory,
SubstitutionModel evolutionaryModel,
LMSSolver solver)
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Uses of SubstitutionModel in pal.tree |
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Constructors in pal.tree with parameters of type SubstitutionModel | |
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SimulatedAlignment.Factory(int sequenceLength,
SubstitutionModel model)
|
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SimulatedAlignment(int sites,
Tree t,
SubstitutionModel m)
Inititalisation |
Uses of SubstitutionModel in pal.treesearch |
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Methods in pal.treesearch with parameters of type SubstitutionModel | |
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UnrootedMLSearcher |
BranchAccess.attach(Node subTree,
Alignment fullAlignment,
SubstitutionModel model)
Create a new Tree Searcher with a new sub tree attached |
UnrootedMLSearcher |
BranchAccess.attach(java.lang.String newSequence,
Alignment fullAlignment,
SubstitutionModel model)
Create a new Tree Searcher with a new sub tree attached |
Tree |
TreeSearchTool.basicUnrootedTreeMLSearch(Alignment a,
SubstitutionModel sm,
boolean optimiseModel)
Do a basic tree search using maximum likelihood on an unrooted tree space, without a given starting tree |
Tree |
TreeSearchTool.basicUnrootedTreeMLSearch(Alignment a,
SubstitutionModel sm,
boolean optimiseModel,
AlgorithmCallback callback)
Do a basic tree search using maximum likelihood on an unrooted tree space, without a given starting tree |
Tree |
TreeSearchTool.basicUnrootedTreeMLSearch(Tree baseTree,
Alignment a,
SubstitutionModel sm,
boolean optimiseModel)
Do a basic tree search using maximum likelihood on an unrooted tree space, with a given starting tree |
Tree |
TreeSearchTool.basicUnrootedTreeMLSearch(Tree baseTree,
Alignment a,
SubstitutionModel sm,
boolean optimiseModel,
AlgorithmCallback callback)
Do a basic tree search using maximum likelihood on an unrooted tree space, with a given starting tree |
static double |
TreeSearchTool.calculateLogLikelihood(Tree tree,
Alignment alignment,
SubstitutionModel model)
Calculate the log likelihood of a particular set of phylogenetic data |
static Alignment |
TreeSearchTool.getMatchingDataType(Alignment alignment,
SubstitutionModel model)
Creates a new alignment that has a compatible data type with a substution model (needed for likelihood stuff) |
static Tree |
TreeSearchTool.optimiseClockConstrainedFixed(Tree tree,
Alignment alignment,
SubstitutionModel model,
boolean optimiseModel,
AlgorithmCallback callback)
Optimise the branches of a tree with regard to maximum likelihood, with the contraints of a global molecular clock - that is, all the tips terminate at the same point. |
static Tree |
TreeSearchTool.optimiseUnrootedFixed(Tree tree,
Alignment alignment,
SubstitutionModel model,
boolean optimiseModel)
Optimise the branches of a tree with regard to maximum likelihood, with no constraints on the branchlengths (as for an unrooted tree). |
static Tree |
TreeSearchTool.optimiseUnrootedFixed(Tree tree,
Alignment alignment,
SubstitutionModel model,
boolean optimiseModel,
AlgorithmCallback callback)
Optimise the branches of a tree with regard to maximum likelihood, with no constraints on the branchlengths (as for an unrooted tree). |
Constructors in pal.treesearch with parameters of type SubstitutionModel | |
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UnrootedMLSearcher(Alignment alignment,
SubstitutionModel model)
Build an unconstrained optimiser based on a randomly generated tree. |
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UnrootedMLSearcher(Alignment alignment,
SubstitutionModel model,
LHCalculator.Factory calcFactory)
|
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UnrootedMLSearcher(Node root,
Alignment alignment,
SubstitutionModel model)
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UnrootedMLSearcher(Node root,
Alignment alignment,
SubstitutionModel model,
LHCalculator.Factory calcFactory)
|
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UnrootedMLSearcher(Node root,
SubstitutionModel model)
Create a searcher based on a given tree, that has no alignment specified (useful as backbone tree for attaching new nodes) |
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UnrootedMLSearcher(Tree t,
Alignment alignment,
SubstitutionModel model)
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