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pomp: statistical inference for
partially-observed Markov processes

News blog

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version 3.0.1.0 available on github

12 June 2020

pomp version 3.0.1.0 has been released: source code and binaries are available. This is a development release, anticipatory to the next CRAN version, which will be 3.1.

From this version, pomp requires at least version 4.0 of R.

New features

A new sequential importance sampling algorithm has been implemented as wpfilter. This is a generalization of the algorithm in pfilter in that it tracks the weights of the particles and allows the user to customize the resampling scheme. In particular, one can determine when resampling happens using the trigger option. One sets trigger to a positive number: when the effective sampling size is less than trigger * Np, resampling is triggered. Thus setting trigger = 0 forbids resampling, while setting trigger to any number ≥0 forces resampling at every observation a la pfilter.

One can also determine the weight distribution of the resampled particles using the target option. One sets target to a number in [0,1]. If target = α, say, and the weight of the i-th particle is w_i, then it is resampled with weight w_i^1-α and, after resampling, carries weight w_i^α.

Thus, setting trigger = 1 and target = 0 reproduces the behavior of pfilter.

The new function wpfilter should be considered an alpha release: both the interface and the underlying algorithms may change at any time without notice. Please explore the function and give feedback via the pomp issues page.

For more information, see the help pages in the package manual.

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version 3.0.0.0 available on github

02 June 2020

pomp version 3.0.0.0 has been released: source code and binaries are available. This is a development release, anticipatory to the next CRAN version, which will be 3.1.

Important Changes

• In mif2, the specification of particle numbers, Np, has changed. When Np is supplied as a function, Np(0) is the requested number of particles at the beginning of the time series. The previous behavior was that Np(1) specified the requested number of particles. This behavior now matches that of the other particle filtering algorithms, pfilter, bsmc2, and pmcmc.

• As promised from version 2.4.1, the tol and max.fail arguments have been removed completely from all particle-filtering algorithms, including pfilter, pmcmc, bsmc2, and mif2. See the older post for more information.

• bsmc2 can now accept a variable number of particles, as do the other particle-filter based algorithms pfilter, pmcmc, and mif2.

• The internal systematic_resample function now allows the user to specify the number of samples desired. Previously, these were always equal to the number of weights supplied.

• The long-deprecated functions onestep.dens, onestep.sim, discrete.time.sim, euler.sim, gillespie.sim, gillespie.hl.sim, conv.rec, and values have been removed. These have been replaced as follows.

  onestep.dens	direct specification of dprocess component
  onestep.sim	onestep
  discrete.time.sim	discrete_time
  euler.sim	euler
  gillespie.sim	gillespie
  gillespie.hl.sim	gillespie_hl
  conv.rec	traces
  values	as.data.frame or as(x,"data.frame")

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version 2.8 released

11 April 2020

pomp version 2.8 has been released to CRAN and is on its way to a mirror near you.

Important Changes

• As promised with version 2.4.1.3, the default value of tol in the particle-filtering algorithms pfilter, pmcmc, mif2, and bsmc2 has been changed to zero. A warning continues to be issued if tol is set to anything other than 0. In a future release, the option to choose a nonzero tolerance will be removed entirely. This change is not backward compatible. If precise reproduction of old results is needed, set the tol parameter to the appropriate nonzero value.

• In traces and diagnostic plotting methods, the nfail variable (tracking numbers of filtering failures) has been dropped.

Minor change

• The Euler step size in sir is now adjustable by means of the argument `delta

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version 2.7.2.1 available on github

04 April 2020

Version 2.7.2.1 is now available on the pomp github repo. This release contains several minor revisions. Install it by doing, e.g., install.packages("pomp",repos="https://kingaa.github.io")

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version 2.7.1.0 available on github

27 March 2020

Version 2.7.1.0 makes the first set of changes to the behavior of particle-filter-based algorithms promised in version 2.4.1.0. In particular, the default value of the tol parameter is now set to zero. This affects the pfilter, mif2, pmcmc, and bsmc2 functions.

See the earlier blog post for more information.

If you haven’t changed your workflow to use tol=0, as prompted by the warnings from versions 2.4.1 on, this change may break some of your existing code. To recover previous behavior, set tol to a positive value (the old default was 10^-17). It is a good idea at this stage, however, to modify your workflows by setting tol=0 or, better still, leaving tol at the default value, since the tol argument will go away soon.

In a forthcoming release, the option to set a nonzero tolerance will be removed entirely.

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