Comments (3)
That is, we can pass whatever density, but the noise is added according to the definition in the dynamics function we pass?
Correct, this filter was added later, and the dynamics density is following along just to match the interface of the other filters. The dynamics_density
field of the advanced filter has a default value set to an arbitrary `Normal() distribution so that it does not have to be provided by the user.
from lowlevelparticlefilters.jl.
I think you might be looking for the AdvancedParticleFilter
type? The standard ParticleFilter
does assume additive noise, an assumption that is lifted by the AdvancedParticleFilter
type. See the docs or the Advanced tutorial for an example of how it's used.
from lowlevelparticlefilters.jl.
Ah, my apologies, I didn't see the propagate_particles!
function for pf::AdvancedParticleFilter
. When creating the AdvancedParticleFilter
object, the dynamics_density
does not get used then, right? That is, we can pass whatever density, but the noise is added according to the definition in the dynamics
function we pass?
from lowlevelparticlefilters.jl.
Related Issues (20)
- Struct of Arrays and BLAS2->3 optimization HOT 1
- Dependency Deprecated - Yeppp HOT 9
- TagBot trigger issue HOT 32
- notation + documentation HOT 2
- v3.0
- Ensemble Kalman filters? HOT 2
- Support for non-uniform observations? HOT 8
- Typo in DAEUnscentedKalmanFilter docstring
- LowLevelParticleFilters won't compile on Julia 1.8/macOS HOT 4
- Incremental precomiplation fatally broken HOT 1
- More flexible noise in UKF
- Next major version
- Compatibility to ModelingToolkit.jl? HOT 4
- Observed variables HOT 2
- Installing this package is downgrading many other packages
- Improve documentation HOT 4
- Particle filter with second order Markov model HOT 3
- loglik bug for ParticleFilter with resampling
- Does `correct!()` support `missing` samples as explained in docs? HOT 4
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from lowlevelparticlefilters.jl.