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pomp: statistical inference for
partially-observed Markov processes

News blog

pomp version 2.1 released to CRAN

01 June 2019

I have just released pomp version 2.1 to CRAN. For the last six months, this has been available on the pomp website as the package pomp2.

Because it is not fully backward-compatible, pomp version 2 is being made available temporarily as the pomp2 package. Hopefully, most of you will have been using pomp2 for some time now, but if you find yourself needing to update old codes and workflows for the new version, have a look at the upgrade guide, which summarizes all the changes in version 2.

If you have pomp2 on your system, you should now remove it entirely, and replace all references to pomp2 in your codes with references to pomp.

As always, please don’t hesitate to bring questions, conundrums, puzzles, paradoxes, bugs, and feature requests, to my attention via by raising an Issue.

Upgrade Guide updates

23 December 2018

The pomp Version 2 Upgrade Guide has been revised. It now includes before-and-after examples of codes rewritten for pomp version 2. This is meant to help you revise pomp version <2 codes to take advantage of the new features.

As a reminder, an alpha-release preview of pomp version 2 is available as pomp2 on the pomp website. Do

install.packages("pomp2",repos="https://kingaa.github.io")

to install it. It is possible to have both pomp (version <2) and pomp2 installed simultaneously during workflow migration.

Around the middle of 2019, pomp2 will be renamed pomp and uploaded to CRAN as version 2.1. From that point forward, there will be no support for older versions of pomp.

Getting Started with pomp2

22 December 2018

The “Getting Started with pomp” vignette has been completely rewritten for pomp version 2. If you are new to pomp, or want to get up to speed on the changes coming in pomp version 2, have a look! The vignette is available here.

pomp version 2 released as pomp2

15 December 2018

Version 2 of pomp, with major improvements, is on its way! Because it is not fully backward-compatible, pomp version 2 is being made available temporarily as the pomp2 package. pomp2 is not available on CRAN but source and binaries can be downloaded from the pomp website. See the installation page for instructions.

pomp2 will be phased out, replaced by version 2 of pomp, around the middle of 2019. At that point, pomp versions <2 will no longer be supported.

It is recommended that users begin making the transition to version 2 now. An upgrade guide is available to help you transition your codes to the new version. In the interim period, you can have both pomp and pomp2 installed on your system simultaneously.

pomp version 1.19 released

14 December 2018

pomp version 1.19 is now available on CRAN. Source and binaries will soon be visible on a CRAN mirror near you.

Important note

Version 2 of pomp, with major improvements, is on its way. Because it is not fully backward-compatible, pomp version 2 is being made available temporarily as the pomp2 package. pomp2 is not available on CRAN but source and binaries can be downloaded from the pomp website. See the installation page for instructions.

pomp2 will be phased out, replaced by version 2 of pomp, around the middle of 2019. At that point, pomp versions <2 will no longer be supported.

It is recommended that users begin making the transition to version 2 now. An upgrade guide is available to help you transition your codes to the new version. In the interim period, you can have both pomp and pomp2 installed on your system simultaneously.

Release notes

pomp version 1.19 includes bug fixes and some feature enhancements.

User-visible changes

• show and print methods have been made very terse: they simply report on the class of the object in question. To see more detailed information about a pomp object, use spy.
• New verbose option in trajectory gives diagnostic information from deSolve integration routines. Of course, this is pertinent only if the model skeleton is a vectorfield.
• coef(object) <- NULL, where object is of class pomp, erases any parameters stored in object.
• The obs and states arguments of simulate are deprecated and will be removed in a forthcoming release.
• The old forward and inverse options for the dir argument of partrans have been dispensed with. The much more descriptive options toEstimationScale and fromEstimationScale remain.
• The euler.sir, gillespie.sir, blowflies, ricker, bbs, dacca, and rw2 examples are all now implemented using C snippets.
• The handling of dprocess has changed. The onestep.dens plugin is now deprecated and will soon be removed. dprocess is now specified directly using either a C snippet or an R function, in much the same way that, for example, dmeasure is specified.
• A bug in pfilter (and hence pmcmc) when filter.traj=TRUE was discovered and fixed. In the buggy version, the filter trajectory was sampled with incorrect weights.
• A bug in the display of istate when deSolve::ode errors has been fixed.
• Timo Voipio contributed a pull request that traps the error resulting from sannbox being passed a candidate.dist that is not a function.

API and implementation changes

• The C-level interface for apply_probe_sims has changed: the new argument rho must be the "package:pomp" environment.
• New (unexported) solibs<- method allows developers of packages extending pomp to incorporate C snippets into object that contain pomp objects.
• New hitch function facilitates construction of pomp.fun objects from R functions, C snippets, and links to external libraries.
• Native routines needed to access pomp.fun objects in C are now registered for use by other packages.
• A new pomp_defines.h header is provided for developers of packages that depend on pomp.
• Internally, rprocess is no longer stored as an R function. The use of plugins is now required for the implementation of the rprocess component. Currently, there are five plugins available: onestep.sim, discrete.time.sim, euler.sim, gillespie.sim, and gillespie.hl.sim.
• The C snippet compiling facilities have been thoroughly reworked.

See the package NEWS for more details.

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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.

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