The Getting started with pomp tutorial has been substantially improved.
In particular, the tutorial now contains not only an example of the construction of a pomp object, but also
- the construction of a likelihood profile using parallelized
mif2computations, - the estimation of a posterior probability density using
pmcmc, including the use of an adaptive proposal distribution (mvn.rw.adaptive) and the estimation of smoothed state trajectories (usingfilter.traj).
Although the tutorial uses as its example a very simple data analysis (one in fact for which far simpler methods than the ones employed would be sufficient), the methods that it illustrates can be readily transposed for dealing with much more challenging problems.
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This software has been made possible by support from the U.S. National Science Foundation (Grants #EF-0545276, #EF-0430120), by the “Inference for Mechanistic Models” Working Group supported by the National Center for Ecological Analysis and Synthesis (a Center funded by N.S.F. (Grant #DEB-0553768), the University of California, Santa Barbara, and the State of California), and by the RAPIDD program of the Science & Technology Directorate, Department of Homeland Security and the Fogarty International Center, U.S. National Institutes of Health. |