Package pal.eval

Class LikelihoodOptimiser

java.lang.Object
pal.eval.LikelihoodOptimiser

public class LikelihoodOptimiser extends Object
  • Constructor Details

  • Method Details

    • optimiseLogLikelihood

      public double optimiseLogLikelihood(Parameterized parameters, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor)
    • optimiseLogLikelihood

      public double optimiseLogLikelihood(Parameterized parameters, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits)
    • optimiseCombined

      public static final double 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. That is, model and tree are optimised concurrently.
      Parameters:
      tree - The tree to be optimised (will be altered by optimisation)
      alignment - The alignment related to tree
      model - The substitution model to be optimised (will be altered by optimisation)
      fxFracDigits - The number of decimal placess to stabilise to in the log likelihood
      xFracDigits - The number of decimal placess to stabilise to in the model/tree parameters
      minimiser - The MultivariateMinimum object that is used for minimising
      monitor - A minimiser monitor to monitor progress
      Returns:
      The maximal log likelihood found
    • optimiseCombined

      public static final double optimiseCombined(ParameterizedTree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits)
      Optimise parameters to acheive maximum likelihood using a combined stategy. That is, model and tree are optimised concurrently.
      Parameters:
      tree - The tree to be optimised (will be altered by optimisation)
      alignment - The alignment related to tree
      model - The substitution model to be optimised (will be altered by optimisation)
      fxFracDigits - The number of decimal placess to stabilise to in the log likelihood
      xFracDigits - The number of decimal placess to stabilise to in the model/tree parameters
      minimiser - The MultivariateMinimum object that is used for minimising
      Returns:
      The maximal log likelihood found
    • optimiseAlternate

      public static final double optimiseAlternate(ParameterizedTree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits)
      Optimise parameters to acheive maximum likelihood using an alternating stategy. That is first the model is optimised, than the tree branch lengths, then the model, then the tree, and so on until convergence.
      Parameters:
      tree - The tree to be optimised (will be altered by optimisation)
      alignment - The alignment related to tree
      model - The substitution model to be optimised (will be altered by optimisation)
      fxFracDigits - The number of decimal placess to stabilise to in the log likelihood
      xFracDigits - The number of decimal placess to stabilise to in the model/tree parameters
      minimiser - The MultivariateMinimum object that is used for minimising
      Returns:
      The maximal log likelihood found
    • optimiseAlternate

      public static final double 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. That is first the model is optimised, than the tree branch lengths, then the model, then the tree, and so on until convergence.
      Parameters:
      tree - The tree to be optimised (will be altered by optimisation)
      alignment - The alignment related to tree
      model - The substitution model to be optimised (will be altered by optimisation)
      fxFracDigits - The number of decimal placess to stabilise to in the log likelihood
      xFracDigits - The number of decimal placess to stabilise to in the model/tree parameters
      minimiser - The MultivariateMinimum object that is used for minimising
      monitor - A minimiser monitor to monitor progress
      Returns:
      The maximal log likelihood found
    • optimiseTree

      public static final double 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.
      Parameters:
      tree - The tree to be optimised (will be altered by optimisation)
      alignment - The alignment related to tree
      model - The substitution model to be optimised (will *not * be altered by optimisation)
      fxFracDigits - The number of decimal placess to stabilise to in the log likelihood
      xFracDigits - The number of decimal placess to stabilise to in the model/tree parameters
      minimiser - The MultivariateMinimum object that is used for minimising
      Returns:
      The maximal log likelihood found
    • optimiseTree

      public static final double 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.
      Parameters:
      tree - The tree to be optimised (will be altered by optimisation)
      alignment - The alignment related to tree
      model - The substitution model to be optimised (will *not * be altered by optimisation)
      fxFracDigits - The number of decimal placess to stabilise to in the log likelihood
      xFracDigits - The number of decimal placess to stabilise to in the model/tree parameters
      minimiser - The MultivariateMinimum object that is used for minimising
      monitor - A minimiser monitor to monitor progress
      Returns:
      The maximal log likelihood found
    • optimiseModel

      public static final double 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.
      Parameters:
      tree - The tree to be optimised (will *not* be altered by optimisation)
      alignment - The alignment related to tree
      model - The substitution model to be optimised (will be altered by optimisation)
      fxFracDigits - The number of decimal placess to stabilise to in the log likelihood
      xFracDigits - The number of decimal placess to stabilise to in the model/tree parameters
      minimiser - The MultivariateMinimum object that is used for minimising
      monitor - A minimiser monitor to monitor progress
      Returns:
      The maximal log likelihood found