LinearizationImportanceDistribution

class probnum.filtsmooth.particle.LinearizationImportanceDistribution(dynamics_model, linearization_strategy)

Bases: ImportanceDistribution

Local linearisation importance distribution.

Methods Summary

from_ekf(dynamics_model[, ...])	Create an importance distribution that uses the EKF for proposals.
from_ukf(dynamics_model)	Create an importance distribution that uses the UKF for proposals.
generate_importance_rv(particle, data, t[, ...])	Generate an importance distribution.
log_correction_factor(proposal_state, ...)	Logarithmic correction factor.
process_initrv_with_data(initrv, data, t[, ...])	Process the initial random variable based on data.

Methods Documentation

classmethod from_ekf(dynamics_model, forward_implementation='classic', backward_implementation='classic')

Create an importance distribution that uses the EKF for proposals.

classmethod from_ukf(dynamics_model)

Create an importance distribution that uses the UKF for proposals.

generate_importance_rv(particle, data, t, dt=None, measurement_model=None)

Generate an importance distribution.

log_correction_factor(proposal_state, importance_rv, dynamics_rv, old_weight)

Logarithmic correction factor.

Return type

float

process_initrv_with_data(initrv, data, t, measurement_model=None)

Process the initial random variable based on data.