Package | Description |
---|---|
de.jstacs.sequenceScores.statisticalModels.differentiable |
Provides all
DifferentiableStatisticalModel s, which can compute the gradient with
respect to their parameters for a given input Sequence . |
de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels |
Provides
DifferentiableStatisticalModel s that are directed graphical models. |
de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous |
Provides
DifferentiableStatisticalModel s that are homogeneous, i.e. |
de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture | |
de.jstacs.sequenceScores.statisticalModels.differentiable.mixture |
Provides
DifferentiableSequenceScore s that are mixtures of other DifferentiableSequenceScore s. |
de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif |
Modifier and Type | Class and Description |
---|---|
class |
AbstractVariableLengthDiffSM
This abstract class implements some methods declared in
DifferentiableStatisticalModel based on the declaration
of methods in VariableLengthDiffSM . |
class |
CyclicMarkovModelDiffSM
This scoring function implements a cyclic Markov model of arbitrary order and periodicity for any sequence length.
|
class |
MappingDiffSM
This class implements a
DifferentiableStatisticalModel that works on
mapped Sequence s. |
class |
MarkovRandomFieldDiffSM
This class implements the scoring function for any MRF (Markov Random Field).
|
class |
NormalizedDiffSM
This class makes an unnormalized
DifferentiableStatisticalModel to a normalized DifferentiableStatisticalModel . |
Modifier and Type | Method and Description |
---|---|
AbstractDifferentiableStatisticalModel |
AbstractDifferentiableStatisticalModel.clone() |
Modifier and Type | Class and Description |
---|---|
class |
BayesianNetworkDiffSM
This class implements a scoring function that is a moral directed graphical
model, i.e.
|
class |
MarkovModelDiffSM
This class implements a
AbstractDifferentiableStatisticalModel for an inhomogeneous Markov model. |
Modifier and Type | Class and Description |
---|---|
class |
HomogeneousDiffSM
This is the main class for all homogeneous
DifferentiableSequenceScore s. |
class |
HomogeneousMM0DiffSM
This scoring function implements a homogeneous Markov model of order zero
(hMM(0)) for a fixed sequence length.
|
class |
HomogeneousMMDiffSM
This scoring function implements a homogeneous Markov model of arbitrary
order for any sequence length.
|
class |
UniformHomogeneousDiffSM
This scoring function does nothing.
|
Modifier and Type | Class and Description |
---|---|
class |
LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
Class for a sparse local inhomogeneous mixture (Slim) model.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractMixtureDiffSM
This main abstract class for any mixture scoring function (e.g.
|
class |
MixtureDiffSM
This class implements a real mixture model.
|
class |
StrandDiffSM
This class enables the user to search on both strand.
|
class |
VariableLengthMixtureDiffSM
This class implements a mixture of
VariableLengthDiffSM by extending MixtureDiffSM and implementing the methods of VariableLengthDiffSM . |
Modifier and Type | Class and Description |
---|---|
class |
DurationDiffSM
This class is the super class for all one dimensional position scoring functions that can be used as durations for semi Markov models.
|
class |
ExtendedZOOPSDiffSM
This class handles mixtures with at least one hidden motif.
|
class |
MixtureDurationDiffSM
This class implements a mixture of
DurationDiffSM s. |
class |
PositionDiffSM
This class implements a position scoring function that enables the user to get a score without using a Sequence
object.
|
class |
SkewNormalLikeDurationDiffSM
This class implements a skew normal like discrete truncated distribution.
|
class |
UniformDurationDiffSM
This scoring function implements a uniform distribution for positions.
|