Uses of Class
pal.math.MultivariateMinimum

Packages that use MultivariateMinimum
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   
 

Uses of MultivariateMinimum in pal.eval
 

Methods in pal.eval with parameters of type MultivariateMinimum
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
 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
 MultivariateMinimum MultivariateMinimum.Factory.generateNewMinimiser()
          Generate a new Multivariate Minimum
 

Uses of MultivariateMinimum in pal.treesearch
 

Methods in pal.treesearch with parameters of type MultivariateMinimum
 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 group
 double 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 group
 double GeneralConstraintGroupManager.optimiseSecondaryGlobalClockConstraints(MultivariateMinimum minimiser, GeneralConstraintGroupManager.LikelihoodScoreAccess scoreAccess, int fxFracDigits, int xFracDigits, MinimiserMonitor rateMonitor)
          Optimise the global clock parameters marked as secondary related to this group
 double GeneralLikelihoodSearcher.optimiseSubstitutionModels(MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor)