pf
svol_apf< nparts, dimx, dimy, resampT > Class Template Reference
Inheritance diagram for svol_apf< nparts, dimx, dimy, resampT >:
Collaboration diagram for svol_apf< nparts, dimx, dimy, resampT >:

Public Types

using ssv = Eigen::Matrix< double, dimx, 1 >
 
using osv = Eigen::Matrix< double, dimy, 1 >
 
- Public Types inherited from APF< nparts, dimx, dimy, resampT >
using ssv = Eigen::Matrix< double, dimx, 1 >
 
using osv = Eigen::Matrix< double, dimy, 1 >
 
using Mat = Eigen::Matrix< double, dimx, dimx >
 
using arrayDouble = std::array< double, nparts >
 
using arrayVec = std::array< ssv, nparts >
 
using arrayUInt = std::array< unsigned int, nparts >
 

Public Member Functions

 svol_apf (const double &phi, const double &beta, const double &sigma)
 
double logMuEv (const ssv &x1)
 Evaluates the log of mu. More...
 
ssv propMu (const ssv &xtm1)
 Evaluates the proposal distribution taking a Eigen::Matrix<double,dimx,1> from the previous time's state, and returning a state for the current time. More...
 
ssv q1Samp (const osv &y1)
 Samples from q1. More...
 
ssv fSamp (const ssv &xtm1)
 Samples from f. More...
 
double logQ1Ev (const ssv &x1, const osv &y1)
 Evaluates the log of q1. More...
 
double logGEv (const osv &yt, const ssv &xt)
 Evaluates the log of g. More...
 
- Public Member Functions inherited from APF< nparts, dimx, dimy, resampT >
 APF (const unsigned int &rs=1)
 The constructor. More...
 
double getLogCondLike () const
 Get the latest log conditional likelihood. More...
 
std::vector< MatgetExpectations () const
 return all stored expectations (taken with respect to $p(x_t|y_{1:t})$ More...
 
void filter (const osv &data, const std::vector< std::function< const Mat(const ssv &)> > &fs=std::vector< std::function< const Mat(const ssv &)> >())
 Use a new datapoint to update the filtering distribution (or smoothing if pathLength > 0). More...
 

Public Attributes

double m_phi
 
double m_beta
 
double m_sigma
 
UnivNormSampler m_stdNormSampler
 

Additional Inherited Members

- Protected Attributes inherited from APF< nparts, dimx, dimy, resampT >
std::array< ssv, nparts > m_particles
 particle samples
 
std::array< double, nparts > m_logUnNormWeights
 particle unnormalized weights
 
unsigned int m_now
 curren time
 
double m_logLastCondLike
 log p(y_t|y_{1:t-1}) or log p(y1)
 
unsigned int m_rs
 the resampling schedule
 
resampT m_resampler
 resampler object (default ctor'd)
 
k_gen< nparts > m_kGen
 k generator object (default ctor'd)
 
std::vector< Matm_expectations
 expectations E[h(x_t) | y_{1:t}] for user defined "h"s
 

Member Function Documentation

template<size_t nparts, size_t dimx, size_t dimy, typename resampT >
auto svol_apf< nparts, dimx, dimy, resampT >::fSamp ( const ssv &  xtm1)
virtual

Samples from f.

Parameters
xtm1a Eigen::Matrix<double,dimx,1> representing the previous time's state.
Returns
a Eigen::Matrix<double,dimx,1> state sample for the current time.

Implements APF< nparts, dimx, dimy, resampT >.

template<size_t nparts, size_t dimx, size_t dimy, typename resampT >
double svol_apf< nparts, dimx, dimy, resampT >::logGEv ( const osv &  yt,
const ssv &  xt 
)
virtual

Evaluates the log of g.

Parameters
yta Eigen::Matrix<double,dimy,1> representing time t's data observation.
xta Eigen::Matrix<double,dimx,1> representing time t's state.
Returns
a double evaluation.

Implements APF< nparts, dimx, dimy, resampT >.

template<size_t nparts, size_t dimx, size_t dimy, typename resampT >
double svol_apf< nparts, dimx, dimy, resampT >::logMuEv ( const ssv &  x1)
virtual

Evaluates the log of mu.

Parameters
x1a Eigen::Matrix<double,dimx,1> representing time 1's state.
Returns
a double evaluation.

Implements APF< nparts, dimx, dimy, resampT >.

template<size_t nparts, size_t dimx, size_t dimy, typename resampT >
double svol_apf< nparts, dimx, dimy, resampT >::logQ1Ev ( const ssv &  x1,
const osv &  y1 
)
virtual

Evaluates the log of q1.

Parameters
x1a Eigen::Matrix<double,dimx,1> representing time 1's state.
y1a Eigen::Matrix<double,dimy,1> representing time 1's data observation.
Returns
a double evaluation.

Implements APF< nparts, dimx, dimy, resampT >.

template<size_t nparts, size_t dimx, size_t dimy, typename resampT >
auto svol_apf< nparts, dimx, dimy, resampT >::propMu ( const ssv &  xtm1)
virtual

Evaluates the proposal distribution taking a Eigen::Matrix<double,dimx,1> from the previous time's state, and returning a state for the current time.

Parameters
xtm1a Eigen::Matrix<double,dimx,1> representing the previous time's state.
Returns
a Eigen::Matrix<double,dimx,1> representing a likely current time state, to be used by the observation density.

Implements APF< nparts, dimx, dimy, resampT >.

template<size_t nparts, size_t dimx, size_t dimy, typename resampT >
auto svol_apf< nparts, dimx, dimy, resampT >::q1Samp ( const osv &  y1)
virtual

Samples from q1.

Parameters
y1a Eigen::Matrix<double,dimy,1> representing time 1's data point.
Returns
a Eigen::Matrix<double,dimx,1> sample for time 1's state.

Implements APF< nparts, dimx, dimy, resampT >.


The documentation for this class was generated from the following file: