Questions tagged [sequential-monte-carlo]
The sequential-monte-carlo tag has no usage guidance.
41
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Metropolis-Hastings algorithm doesn't converge to the global minimum
I calculated the total root mean squared error of 24 parameters that are estimated with metropolis hastings, I ran the algorithm for 100.000 iterations, and as the chain forward it reached a global ...
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17
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Decompose variance explained in sequential mediation in lavaan
I am using sequential mediation analyses (aka serial mediation) in lavaan in R.
Below is my model
...
- 1
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23
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SMC sampler weights when $K_n$ leaves $\pi_{n-1}$ invariant
I cannot seem to find this proof anywhere. Suppose I choose $K_n$ to leave $\pi_{n-1}$ invariant, and $L_{n-1}$ to be the reversal kernel. I want to show that the incremental weights
$$
w_n(x_{n-1}, ...
- 657
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37
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How to mitigate large sample number for multimodal posteriors in Approximate Bayesian Computation-Sequential Monte Carlo (ABC-SMC)?
I want to do Bayesian inference for a model function for which the likelihood cannot be explicitly computed, which is why I turned to Approximate Bayesian Computation (ABC). In particular, I am using ...
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Some Problems in Auxiliary Particle Filter
recently I am studying PF. And I am stuck in APF for a few days, though I derived many times. Here is my question:
I followed the framework of this paper. The APF is defined in Algorithm 1:
The ...
- 95
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56
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Why do we want to minimise the variance of our importance weights in SIS with respect to the proposal distribution
Is there a clear and precise explanation of why minimising the variance of the weights in SIS with respect to a proposal ensures that the samples generated from the empirical distribution induced by ...
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46
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Do Sequential Monte Carlo simulations degenerate when you chain them together?
Context: Suppose that I run a Sequential Monte Carlo simulation with likelihood tempering to perform parameter inference on a filtering problem. This takes me from my (unspecified) prior distribution ...
- 467
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103
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Bayesian evidence with Sequential Monte Carlo and an unnormalized likelihood function: a contradiction?
There is a contradiction in my understanding of Sequential Monte Carlo for estimating Bayesian evidence for model comparison:
Marginal likelihood (aka normalizing constant, aka Bayesian evidence) ...
- 467
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0
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85
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Difference in Normalizing constants for Annealed Importance Sampling and Sequential Monte Carlo
I have been looking into Annealed Importance Sampling (AIS, Neal, 2001) and Sequential Monte Carlo (SMC, Del Moral et al., 2006) methods lately. I was wondering where the difference in estimating the ...
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79
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Computing mean of filtering and smoothing distributions from a particle filter
Suppose I have a model with latent states $x_1, x_2, \ldots x_T$ and observations $y_1, y_2, \ldots y_T$. I run a sequential monte carlo algorithm to give me the following approximation to $p(x_{1:T} |...
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42
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Is there a Sequential Gaussian Simulation that uses Ordinary Kriging?
As far as I have read, Sequential Gaussian Simulation always uses Simple Kriging. Is there any chance that it uses Ordinary Kriging?
- 11
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226
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Sequential recommendation: how to effective encoding output item?
Now I am learning about sequential recommendation - session based recommendation. I have understood that User-item interactions may be viewed as sequential action (first I clicked item A, then click ...
- 150
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107
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ABC-SMC, how to obtain summary statistics
I'm using the package pyABC which implements the ABC-SMC algorithm. My model is described by fewer than 10 parameters.
I run the code with $N=50$ particles and stop the process after a maximum run ...
- 4,352
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1
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98
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Particle Filter Derivation based on Forward Algorithm
I have been studying the particle filter, sequential monte carlo methods, and sequential importance sampling.
I am interested in apply the particle filter equations to the standard forward algorithm:
$...
- 217
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1
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166
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SMC Samplers - Optimal Backward Kernel Explanation
In Sequential Monte Carlo Samplers of Del Moral (2006) we see that the optimal backward kernel is
$$
L_{n-1}^{\text{opt}} (x_{n-1} \mid x_n) = \frac{\eta_{n-1}(x_{n-1}) K_n(x_n \mid x_{n-1})}{\eta_n(...
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