Version 1.0.0 by Lawrence Murray
Periodic drift process for diffusion bridge sampling.
This simulates a number of data sets for testing and fits the bridge weight function. GNU Octave is required. Running it is optional, as a number of simulated data sets are already included.
This runs a particle filter as well as samples from the posterior distribution for a fixed data set of four observations given in Lin, Chen & Mykland (2010).
This runs tests on the bootstrap and bridge particle filters on the simulated data sets. Alternatively, these tests may be run as an array job on a cluster:
qsub -t 0-15 qsub_test_bridge.sh qsub -t 0-15 qsub_test_bootstrap.sh qsub -t 0-15 qsub_test_exact.sh
The last line computes normalising constants to be used as “exact” values when computing the MSE metric for comparison plots.
Finally, results may be plot with:
octave --path oct/ --eval "plot_and_print"
GNU Octave and OctBi are required.
Note that, as of version 1.1.0 of LibBi, running any of these gives the warnings:
Warning (line 29): 'obs' variables should not appear on the right side of actions in the 'transition' block. Warning (line 42): 'obs' variables should not appear on the right side of actions in the 'lookahead_transition' block.
This is normal.
This package implements the periodic drift diffusion process introduced in Beskos et al. (2006) and further studied in Lin, Chen & Mykland (2010). The form of the process model is the Ito stochastic differential equation:
The task is to simulate diffusion bridges between the observed values. It was used as a test case in Del Moral & Murray (2014). The package may be used to reproduce the results in that paper.
Beskos, A.; Papaspiliopoulos, O.; Roberts, G. & Fearnhead, P. Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes. Journal of the Royal Statistical Society Series B, 2006, 68, 333-382.
Del Moral, P. & Murray, L. M. Sequential Monte Carlo with Highly Informative Observations, 2014. [arXiv]
Lin, M.; Chen, R. & Mykland, P. On Generating Monte Carlo Samples of Continuous Diffusion Bridges. Journal of the American Statistical Association, 2010, 105, 820-838.