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_data/biblio.yml

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author: "M. Domenech de Cellès and P. Rohani"
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year: "2024"
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title: "Pertussis vaccines, epidemiology and evolution"
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journal: "Nature Reviews Microbiology"
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journal: "Nat Rev Microbiol"
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doi: "https://doi.org/10.1038/s41579-024-01064-8"
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- key: Domeyer2022
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year: "2024"
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title: "Modelling the unexpected dynamics of COVID-19 in Manaus, Brazil"
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journal: "Infectious Disease Modelling"
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volume: "9"
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number: "2"
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pages: "557–568"
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doi: "https://doi.org/10.1016/j.idm.2024.02.012"
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- key: Ionides2006

_includes/menu.html

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<ul>
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<li><a id="about" href="{{site.baseurl}}/index.html">About</a></li>
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<li><a id="install" href="{{site.baseurl}}/install.html">Installation</a></li>
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<li><a id="manual" href="{{site.baseurl}}/manual/" target="_blank">Manual</a></li>
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<li><a id="faq" href="{{site.baseurl}}/FAQ.html">FAQ</a></li>
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<li><a id="manual" href="{{site.baseurl}}/manual/" target="_blank">Manual</a></li>
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<li><a id="docs" href="{{site.baseurl}}/docs.html">Documentation</a></li>
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<li><a id="discussions" href="https://github.com/kingaa/pomp/discussions" target="_blank">Discussions</a></li>
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<li><a id="issues" href="https://github.com/kingaa/pomp/issues" target="_blank">Issues</a></li>

index.md

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<span class="firstcharacter">**pomp**</span> provides a very general realization of nonlinear partially-observed Markov processes (also known as nonlinear stochastic dynamical systems, hidden Markov models, and state space models).
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These are a generalization of linear state-space and hidden Markov models to nonlinear, non-Gaussian processes in either discrete or continuous time.
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In **pomp**, one can implement a model by specifying its unobserved process and measurement components;
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Using **pomp**, one can implement a model by specifying its latent-state process and measurement components;
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the package uses these functions in algorithms to simulate, analyze, and fit the model to data.
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Currently, **pomp** provides support for
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- trajectory matching,
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- the approximate Bayesian sequential Monte Carlo algorithm of Liu&nbsp;&amp;&nbsp;West&nbsp;(2001),
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- the particle Markov chain Monte Carlo method of Andrieu et al.&nbsp;(2010),
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- approximate Bayesian computation (ABC; Toni et al.&nbsp;2009)
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- approximate Bayesian computation (ABC; Toni et al.&nbsp;2009),
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- the improved iterated filtering method (Ionides et al. 2015),
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- probe-matching methods based on synthetic likelihood (e.g., Kendall et al. 1999, Wood et al. 2010)
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- the nonlinear forecasting method of Ellner&nbsp;&amp;&nbsp;Kendall,
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- the ensemble Kalman filter of Evensen (1994, 2009), and
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- probe-matching methods based on synthetic likelihood (e.g., Kendall et al. 1999, Wood et al. 2010),
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- the nonlinear forecasting method of Ellner et al. (1998),
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- the ensemble Kalman filter of Evensen (1994, 2009),
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- the ensemble adjustment Kalman filter of Anderson (2001), and
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- power-spectrum-matching methods of Reuman et al. (2006).
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install.md

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# Installation instructions
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There are several easy ways to install the package.
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One can install from CRAN in the usual way or install a usually slightly more up-to-date version from Github.
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Once you've installed the package, follow the instructions below to test the installation.
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On some systems, additional steps may be needed to actualize the full capabilities of the package.
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-------------------
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## Install **pomp**
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### From CRAN:
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Source and binaries are [available on CRAN](http://cran.r-project.org/package=pomp){:target="_blank"}.
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### Download and install locally
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You can also [download the latest release](https://github.com/kingaa/pomp/releases/) and install it locally [as you would any **R** package](https://cran.r-project.org/doc/manuals/r-release/R-admin.html#Installing-packages).
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You can also download the [latest release](https://github.com/kingaa/pomp/releases/) as a source or binary archive and install it locally [as you would any **R** package](https://cran.r-project.org/doc/manuals/r-release/R-admin.html#Installing-packages).
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Alternatively, if the **devtools** package is installed on your system, to build the package from source, you can run:
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```r
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devtools::install_github("kingaa/pomp")
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```
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---------------------------
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### Testing your installation
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## Test your installation
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To make use of **pomp**'s facilities for accelerated computation using compiled C code, and to compile the package from source, you will want the ability to compile C code and dynamically link it into an **R** session.
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To test this, run the following in an **R** session:
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This script attempts to compile a simple C program.
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Upon success, you'll see a "Hello!" message.
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<i>If this fails, consult the instructions below, according to your operating system.</i>
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--------------------------
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*If this fails, consult the instructions below, according to your operating system.*
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### Important note for Windows users
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To use **pomp**'s compilation facility, you need to have the **Rtools** suite installed.
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To use **pomp**'s compilation facility under Windows, you need to have the **Rtools** suite installed.
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This can be [downloaded from CRAN](http://cran.r-project.org/bin/windows/Rtools){:target="_blank"}.
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**Rtools** is needed to obtain full value from **pomp**, but also to compile **R** packages from source, if you ever want to do that.
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```
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On success, you will see two "Hello!" messages.
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------------------------
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### Important note for Mac OS users
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To use **pomp**'s compilation facility, you need to have the <code>Xcode</code> app installed.
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To use **pomp**'s compilation facility under MacOS, you need to have the <code>Xcode</code> app installed.
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<code>Xcode</code> is free and can be installed according to [these instructions](https://mac.r-project.org/tools/){:target="_blank"}.
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In addition, some users report problems installing **pomp** from source due to lack of an appropriate **gfortran** installation, which is not included by default in all versions of **Xcode**.
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```
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On success, you will see two "Hello!" messages.
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------------------------
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### Important note for Linux users
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To install **pomp** from source, you will need the `gfortran` compiler on your machine and will therefore may need to install it.
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To install **pomp** from source, you will need the `gfortran` compiler on your machine and may therefore need to install it.
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To do so on a Debian-based system (e.g., Ubuntu), for example, run:
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```sh
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sudo apt install gfortran

vignettes/pomp.bib

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creationdate = {2024-04-16T12:37:08},
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doi = {10.1038/s41467-024-44943-7},
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file = {:Briga2024.pdf:PDF},
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fjournal = {Nature Communications},
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groups = {pomp, alumni},
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modificationdate = {2024-05-03T07:49:30},
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modificationdate = {2024-07-02T10:36:09},
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}
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@InCollection{Brillinger1980,
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title = {Modelling the unexpected dynamics of {COVID-19} in {Manaus}, {Brazil}},
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year = {2024},
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month = mar,
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number = {2},
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pages = {557--568},
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volume = {9},
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creationdate = {2024-03-12T08:36:49},
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doi = {10.1016/j.idm.2024.02.012},
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groups = {pomp, alumni},
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modificationdate = {2024-03-12T08:36:49},
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modificationdate = {2024-07-02T10:35:10},
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}
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@Article{Houtekamer1998,
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@Article{DomenechdeCelles2024,
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author = {Domenech de Cell{\`{e}}s, Matthieu and Rohani, Pejman},
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journal = {Nature Reviews Microbiology},
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journal = {Nat Rev Microbiol},
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title = {Pertussis vaccines, epidemiology and evolution},
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year = {2024},
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abstract = {Pertussis, which is caused by Bordetella pertussis, has plagued humans for at least 800\hspace{0.167em}years, is highly infectious and can be fatal in the unvaccinated, especially very young infants. Although the rollout of whole-cell pertussis (wP) vaccines in the 1940s and 1950s was associated with a drastic drop in incidence, concerns regarding the reactogenicity of wP vaccines led to the development of a new generation of safer, acellular (aP) vaccines that have been adopted mainly in high-income countries. Over the past 20\hspace{0.167em}years, some countries that boast high aP coverage have experienced a resurgence in pertussis, which has led to substantial debate over the basic immunology, epidemiology and evolutionary biology of the bacterium. Controversy surrounds the duration of natural immunity and vaccine-derived immunity, the ability of vaccines to prevent transmission and severe disease, and the impact of evolution on evading vaccine immunity. Resolving these issues is made challenging by incomplete detection of pertussis cases, the absence of a serological marker of immunity, modest sequencing of the bacterial genome and heterogeneity in diagnostic methods of surveillance. In this Review, we lay out the complexities of contemporary pertussis and, where possible, propose a parsimonious explanation for apparently incongruous observations.},
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creationdate = {2024-07-02T10:15:54},
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doi = {10.1038/s41579-024-01064-8},
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fjournal = {Nature Reviews Microbiology},
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groups = {pomp},
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modificationdate = {2024-07-02T10:15:57},
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modificationdate = {2024-07-02T10:36:09},
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}
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@Article{Kendall1999,
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creationdate = {2024-02-17T14:43:53},
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doi = {10.1073/pnas.2211422120},
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file = {:He2023.pdf:PDF},
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fjournal = {Proceedings of the National Academy of Sciences},
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groups = {alumni, pomp},
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modificationdate = {2024-05-03T07:49:40},
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modificationdate = {2024-07-02T10:36:09},
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}
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@Article{Zhang2021,
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doi = {10.1016/j.euroecorev.2023.104624},
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fjournal = {European economic review},
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groups = {pomp},
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modificationdate = {2024-01-03T15:51:29},
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modificationdate = {2024-07-02T10:36:09},
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owner = {kingaa},
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}
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