Package: panelPomp 1.5.0.0
panelPomp: Inference for Panel Partially Observed Markov Processes
Data analysis based on panel partially-observed Markov process (PanelPOMP) models. To implement such models, simulate them and fit them to panel data, 'panelPomp' extends some of the facilities provided for time series data by the 'pomp' package. Implemented methods include filtering (panel particle filtering) and maximum likelihood estimation (Panel Iterated Filtering) as proposed in Breto, Ionides and King (2020) "Panel Data Analysis via Mechanistic Models" <doi:10.1080/01621459.2019.1604367>.
Authors:
panelPomp_1.5.0.0.tar.gz
panelPomp_1.5.0.0.tar.gz(r-4.5-noble)panelPomp_1.5.0.0.tar.gz(r-4.4-noble)
panelPomp_1.5.0.0.tgz(r-4.4-emscripten)panelPomp_1.5.0.0.tgz(r-4.3-emscripten)
panelPomp.pdf |panelPomp.html✨
panelPomp/json (API)
NEWS
# Install 'panelPomp' in R: |
install.packages('panelPomp', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- twentycities - He et al. 2010 twenty UK cities weekly reported measles data
- uk_measles - Weekly reported measles data for 362 locations in the UK
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 18 days agofrom:f3c18b8254. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 09 2024 |
R-4.5-linux | OK | Dec 09 2024 |
Exports:coefcoef<-contactsget_colget_rowlogLikmif2panel_logmeanexppanelGompertzpanelGompertzLikelihoodpanelMeaslespanelPomppanelRandomWalkpfilterplotprintrunif_panel_designsharedshared<-showsimulatespecificspecific<-toMatrixPparamstoParamListtoParamVectracesunit_objectsunitlogLikunitLogLikwindowwQuotes
Dependencies:clicodadata.tabledeSolvedigestgluelatticelifecyclemvtnormpomprlang
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Inference for PanelPOMPs (Panel Partially Observed Markov Processes) | panelPomp-package |
Coercing 'panelPomp' objects as 'list', 'pompList' or 'data.frame' | as |
Modifying parameters of filtered objects | coef<-,pfilterd.ppomp-method shared<-,pfilterd.ppomp-method specific<-,pfilterd.ppomp-method |
Contacts model | contacts |
Get single column or row without dropping names | get_col get_dim get_row |
PIF: Panel iterated filtering | mif2 mif2,mif2d.ppomp-method mif2,panelPomp-method mif2d.ppomp-class traces,mif2d.ppomp-method |
Handling of loglikelihood replicates | logLik,matrix-method panel_loglik |
Log-mean-exp for panels | panel_logmeanexp |
#' Create design matrix for panelPomp calculations | panel-designs runif_panel_design |
Panel Gompertz model | panelGompertz |
Likelihood for a panel Gompertz model via a Kalman filter | panelGompertzLikelihood |
Make a panelPomp model using UK measles data. | panelMeasles |
Constructing 'panelPomp' objects | panelPomp panelPomp-class |
Manipulating 'panelPomp' objects | coef,panelPomp-method coef<-,panelPomp-method length,panelPomp-method names,panelPomp-method panelPomp_methods print,panelPomp-method shared,panelPomp-method shared<-,panelPomp-method show,panelPomp-method specific,panelPomp-method specific<-,panelPomp-method toParamList unit_objects,panelPomp-method window,panelPomp-method [,panelPomp-method [[,panelPomp-method |
Panel random walk model | panelRandomWalk |
Manipulating 'panelPomp' object parameter formats | params toMatrixPparams toParamVec |
Particle filtering for panel data | logLik,pfilterd.ppomp-method pfilter pfilter,panelPomp-method pfilterd.ppomp-class unitLogLik,pfilterd.ppomp-method |
panelPomp plotting facilities | plot plot,panelPomp_plottable-method |
Simulations of a panel of partially observed Markov process | simulate simulate,panelPomp-method |
He et al. 2010 twenty UK cities weekly reported measles data | twentycities |
Weekly reported measles data for 362 locations in the UK | uk_measles |
Extract Unit Log-Likelihoods | unitlogLik,pfilterd.ppomp-method |