de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.abstracts
Class AbstractMultiObservationDistributionIndep<S extends Copyable<?>,T extends Copyable<?>>

java.lang.Object
  extended by de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.abstracts.AbstractMultiObservationDistribution<S,T>
      extended by de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.abstracts.AbstractMultiObservationDistributionIndep<S,T>
Type Parameters:
S - Type of discrete variables in the multi target observation
T - Type of discrete variables in the multi target state
All Implemented Interfaces:
ConditionalDistribution<AbstractMultiState<T>>, EvaluatableDistribution<AbstractMultiState<S>>, FirstOrderMoment<AbstractMultiState<T>>, IndependentlyEvaluatableDistribution<AbstractMultiState<S>>, LogEvaluatableDistribution<AbstractMultiState<S>>, LogIndependentlyEvaluatableDistribution<AbstractMultiState<S>>, SecondOrderCentralMoment<Jama.Matrix[]>
Direct Known Subclasses:
MultiObsDistributionIndepGaussians, MultiObsDistributionIndepGaussMix

public abstract class AbstractMultiObservationDistributionIndep<S extends Copyable<?>,T extends Copyable<?>>
extends AbstractMultiObservationDistribution<S,T>
implements IndependentlyEvaluatableDistribution<AbstractMultiState<S>>, LogIndependentlyEvaluatableDistribution<AbstractMultiState<S>>, FirstOrderMoment<AbstractMultiState<T>>, SecondOrderCentralMoment<Jama.Matrix[]>

Abstract class for multi target observation distributions. Used in the Bayesian tracking framework. A distribution of this type represents the probability of a multi target observation given a certain multi target state X: p(Z|X) The distribution can be evaluated independently for components in Z

Author:
Oliver Gress

Field Summary
 
Fields inherited from class de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.abstracts.AbstractMultiObservationDistribution
condX, factoryX, factoryZ
 
Constructor Summary
AbstractMultiObservationDistributionIndep(AbstractMultiState<T> conditionX, AbstractMultiStateFactory<T> factoryX, AbstractMultiStateFactory<S> factoryZ)
          Constructor to set the condition conditionX, and the factories of multi state and multi observation variables
 
Method Summary
abstract  int getNumOfIndeps()
           
abstract  double log_p(AbstractMultiState<S> Z)
          Evaluate natural logarithm of p(X) at location x. log(P(X=x))
abstract  double log_p(AbstractMultiState<S> Z, int i)
          Evaluate the density independently for observation i in Z conditional on state i in X
abstract  double log_p(AbstractMultiState<S> Z, int i, int j)
          Evaluate the density independently for observation i in Z conditional on state j in X
abstract  double p(AbstractMultiState<S> Z)
          Evaluate p(X) at location x.
abstract  double p(AbstractMultiState<S> Z, int i)
          Evaluate the density independently for observation i in Z conditional on state i in X
abstract  double p(AbstractMultiState<S> Z, int i, int j)
          Evaluate the density independently for observation i in Z conditional on state j in X
 
Methods inherited from class de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.abstracts.AbstractMultiObservationDistribution
getCondition, setCondition
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 
Methods inherited from interface de.unihalle.informatik.MiToBo.math.distributions.interfaces.FirstOrderMoment
getMean
 
Methods inherited from interface de.unihalle.informatik.MiToBo.math.distributions.interfaces.SecondOrderCentralMoment
getCovariance
 

Constructor Detail

AbstractMultiObservationDistributionIndep

public AbstractMultiObservationDistributionIndep(AbstractMultiState<T> conditionX,
                                                 AbstractMultiStateFactory<T> factoryX,
                                                 AbstractMultiStateFactory<S> factoryZ)
Constructor to set the condition conditionX, and the factories of multi state and multi observation variables

Parameters:
conditionX -
factoryX -
factoryZ -
Method Detail

getNumOfIndeps

public abstract int getNumOfIndeps()

log_p

public abstract double log_p(AbstractMultiState<S> Z)
Description copied from interface: LogEvaluatableDistribution
Evaluate natural logarithm of p(X) at location x. log(P(X=x))

Specified by:
log_p in interface LogEvaluatableDistribution<AbstractMultiState<S extends Copyable<?>>>
Specified by:
log_p in class AbstractMultiObservationDistribution<S extends Copyable<?>,T extends Copyable<?>>
Parameters:
Z - realization of random variable X
Returns:
value of log(p(X)) at x

log_p

public abstract double log_p(AbstractMultiState<S> Z,
                             int i)
Evaluate the density independently for observation i in Z conditional on state i in X

Specified by:
log_p in interface LogIndependentlyEvaluatableDistribution<AbstractMultiState<S extends Copyable<?>>>
Parameters:
Z - realization of random variable X
i - i-th element in x
Returns:
value of log(p_i(X_i)) at x_i

log_p

public abstract double log_p(AbstractMultiState<S> Z,
                             int i,
                             int j)
Evaluate the density independently for observation i in Z conditional on state j in X

Parameters:
x -
i -
j -
Returns:

p

public abstract double p(AbstractMultiState<S> Z)
Description copied from interface: EvaluatableDistribution
Evaluate p(X) at location x. P(X=x)

Specified by:
p in interface EvaluatableDistribution<AbstractMultiState<S extends Copyable<?>>>
Specified by:
p in class AbstractMultiObservationDistribution<S extends Copyable<?>,T extends Copyable<?>>
Parameters:
Z - realization of random variable X
Returns:
value of p(X) at x

p

public abstract double p(AbstractMultiState<S> Z,
                         int i)
Evaluate the density independently for observation i in Z conditional on state i in X

Specified by:
p in interface IndependentlyEvaluatableDistribution<AbstractMultiState<S extends Copyable<?>>>
Parameters:
Z - realization of random variable X
i - i-th element in x
Returns:
value of p_i(X_i) at x_i

p

public abstract double p(AbstractMultiState<S> Z,
                         int i,
                         int j)
Evaluate the density independently for observation i in Z conditional on state j in X

Parameters:
x -
i -
j -
Returns: