Uses of Class
pal.math.MultivariateMinimum
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Packages that use MultivariateMinimum Package Description pal.eval Classes for evaluating evolutionary hypothesis (chi-square and likelihood criteria) and estimating model parameters.pal.math Classes for math stuff such as optimisation, numerical derivatives, matrix exponentials, random numbers, special function etc.pal.treesearch -
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Uses of MultivariateMinimum in pal.eval
Methods in pal.eval with parameters of type MultivariateMinimum Modifier and Type Method Description 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 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.double
LikelihoodOptimiser. optimiseLogLikelihood(Parameterized parameters, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits)
double
LikelihoodOptimiser. optimiseLogLikelihood(Parameterized parameters, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor)
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.double
ChiSquareValue. optimiseParameters(MultivariateMinimum mm)
optimise parameters of a tree by minimising its chi-square value (tree must be a ParameterizedTree)double
LikelihoodValue. optimiseParameters(MultivariateMinimum mm)
optimise parameters of tree by maximising its likelihood (this assumes that tree is a ParameterizedTree)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.double
DemographicValue. optimize(MultivariateMinimum givenMvm)
optimize log-likelihood value and compute corresponding SEs given an optimizer -
Uses of MultivariateMinimum in pal.math
Subclasses of MultivariateMinimum in pal.math Modifier and Type Class Description class
ConjugateDirectionSearch
methods for minimization of a real-valued function of several variables without using derivatives (Brent's modification of a conjugate direction search method proposed by Powell)class
ConjugateGradientSearch
minimization of a real-valued function of several variables using a the nonlinear conjugate gradient method where several variants of the direction update are available (Fletcher-Reeves, Polak-Ribiere, Beale-Sorenson, Hestenes-Stiefel) and bounds are respected.class
DifferentialEvolution
global minimization of a real-valued function of several variables without using derivatives using a genetic algorithm (Differential Evolution)class
GeneralizedDEOptimizer
Provides an general interface to the DifferentialEvolution class that is not tied to a certain number of parameters (as DifferentialEvolution is).class
OrthogonalSearch
minimization of a real-valued function of several variables without using derivatives, using the simple strategy of optimizing variables one by one.Methods in pal.math that return MultivariateMinimum Modifier and Type Method Description MultivariateMinimum
MultivariateMinimum.Factory. generateNewMinimiser()
Generate a new Multivariate Minimum -
Uses of MultivariateMinimum in pal.treesearch
Methods in pal.treesearch with parameters of type MultivariateMinimum Modifier and Type Method Description UndoableAction
UnrootedMLSearcher. getBranchLengthWithModelOptimiseAction(StoppingCriteria.Factory stopper, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits)
UndoableAction
UnrootedMLSearcher. getModelOptimiseAction(MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits)
UndoableAction
UnrootedMLSearcher. getModelOptimiseAction(MultivariateMinimum minimiser, MinimiserMonitor monitor, int fxFracDigits, int xFracDigits)
double
GeneralLikelihoodSearcher. optimiseAllFullHeirarchy(StoppingCriteria mainStopper, StoppingCriteria subStopper, MultivariateMinimum rateMinimiser, int fxFracDigits, int xFracDigits, AlgorithmCallback callback, SearchMonitor monitor, MinimiserMonitor rateMonitor)
double
GeneralConstraintGroupManager. optimiseAllGlobalClockConstraints(MultivariateMinimum minimiser, GeneralConstraintGroupManager.LikelihoodScoreAccess scoreAccess, int fxFracDigits, int xFracDigits, MinimiserMonitor rateMonitor)
Optimise all the global clock parameters related to this groupdouble
GeneralLikelihoodSearcher. optimiseAllPlusSubstitutionModel(StoppingCriteria stopper, MultivariateMinimum rateMinimiser, MultivariateMinimum substitutionModelMinimiser, int fxFracDigits, int xFracDigits, AlgorithmCallback callback, SearchMonitor monitor, int substitutionModelOptimiseFrequency, MinimiserMonitor substitutionModelMonitor, MinimiserMonitor rateMonitor)
double
GeneralLikelihoodSearcher. optimiseAllSimple(StoppingCriteria stopper, MultivariateMinimum rateMinimiser, int fxFracDigits, int xFracDigits, AlgorithmCallback callback)
double
GeneralLikelihoodSearcher. optimiseAllSimple(StoppingCriteria stopper, MultivariateMinimum rateMinimiser, int fxFracDigits, int xFracDigits, AlgorithmCallback callback, SearchMonitor monitor, MinimiserMonitor rateMonitor)
double
GeneralLikelihoodSearcher. optimiseAllSimple(StoppingCriteria stopper, MultivariateMinimum rateMinimiser, int fxFracDigits, int xFracDigits, AlgorithmCallback callback, SearchMonitor monitor, MinimiserMonitor rateMonitor, int groupOptimistionType)
double
GeneralLikelihoodSearcher. optimiseAllSimpleHeirarchy(StoppingCriteria stopper, MultivariateMinimum rateMinimiser, int fxFracDigits, int xFracDigits, AlgorithmCallback callback, SearchMonitor monitor, MinimiserMonitor rateMonitor)
double
GeneralLikelihoodSearcher. optimiseConstraintRateModels(MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor rateMonitor)
double
GeneralConstraintGroupManager. optimisePrimaryGlobalClockConstraints(MultivariateMinimum minimiser, GeneralConstraintGroupManager.LikelihoodScoreAccess scoreAccess, int fxFracDigits, int xFracDigits, MinimiserMonitor rateMonitor)
Optimise the global clock parameters marked as primary related to this groupdouble
GeneralConstraintGroupManager. optimiseSecondaryGlobalClockConstraints(MultivariateMinimum minimiser, GeneralConstraintGroupManager.LikelihoodScoreAccess scoreAccess, int fxFracDigits, int xFracDigits, MinimiserMonitor rateMonitor)
Optimise the global clock parameters marked as secondary related to this groupdouble
GeneralLikelihoodSearcher. optimiseSubstitutionModels(MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor)
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