A B C D E F G H I K L M N O P R S T U V W
pomp-package | Inference for partially observed Markov processes |
abc | Approximate Bayesian computation |
abc-method | Approximate Bayesian computation |
accumvars | accumulator variables |
bake | Tools for reproducible computations |
basic_components | Basic POMP model components. |
basic_probes | Useful probes for partially-observed Markov processes |
betabinomial | Beta-binomial distribution |
blowflies | Nicholson's blowflies. |
blowflies1 | Nicholson's blowflies. |
blowflies2 | Nicholson's blowflies. |
bsflu | Influenza outbreak in a boarding school |
bsmc2 | The Liu and West Bayesian particle filter |
bsmc2-method | The Liu and West Bayesian particle filter |
bsplines | B-spline bases |
bspline_basis | B-spline bases |
c | Concatenate |
c.Pomp | Concatenate |
childhood_disease_data | Historical childhood disease incidence data |
coef | Extract, set, or alter coefficients |
coef-method | Extract, set, or alter coefficients |
coef<- | Extract, set, or alter coefficients |
coef<--method | Extract, set, or alter coefficients |
compartmental_models | Compartmental epidemiological models |
concat | Concatenate |
cond_logLik | Conditional log likelihood |
cond_logLik-method | Conditional log likelihood |
continue | Continue an iterative calculation |
continue-method | Continue an iterative calculation |
covariates | Covariates |
covariate_table | Covariates |
covariate_table-method | Covariates |
covmat | Estimate a covariance matrix from algorithm traces |
covmat-method | Estimate a covariance matrix from algorithm traces |
Csnippet | C snippets |
dacca | Model of cholera transmission for historic Bengal. |
dbetabinom | Beta-binomial distribution |
design | Design matrices for pomp calculations |
deulermultinom | Eulermultinomial and gamma-whitenoise distributions |
dinit | dinit workhorse |
dinit-method | dinit workhorse |
dinit_spec | dinit specification |
discrete_time | rprocess specification |
dmeasure | dmeasure workhorse |
dmeasure-method | dmeasure workhorse |
dmeasure_spec | dmeasure specification |
dprior | dprior workhorse |
dprior-method | dprior workhorse |
dprocess | dprocess workhorse |
dprocess-method | dprocess workhorse |
dprocess_spec | dprocess specification |
eakf | Ensemble Kalman filters |
eakf-method | Ensemble Kalman filters |
ebola | Ebola outbreak, West Africa, 2014-2016 |
ebolaModel | Ebola outbreak, West Africa, 2014-2016 |
ebolaWA2014 | Ebola outbreak, West Africa, 2014-2016 |
eff_sample_size | Effective sample size |
eff_sample_size-method | Effective sample size |
elementary_algorithms | Elementary computations on POMP models. |
emeasure | emeasure workhorse |
emeasure-method | emeasure workhorse |
emeasure_spec | emeasure specification |
enkf | Ensemble Kalman filters |
enkf-method | Ensemble Kalman filters |
estimation_algorithms | Parameter estimation algorithms for POMP models. |
euler | rprocess specification |
eulermultinom | Eulermultinomial and gamma-whitenoise distributions |
ewcitmeas | Historical childhood disease incidence data |
ewmeas | Historical childhood disease incidence data |
expit | Transformations |
filter_mean | Filtering mean |
filter_mean-method | Filtering mean |
filter_traj | Filtering trajectories |
filter_traj-method | Filtering trajectories |
flow | flow workhorse |
flow-method | flow workhorse |
forecast | Forecast mean |
forecast-method | Forecast mean |
freeze | Tools for reproducible computations |
gillespie | rprocess specification |
gillespie_hl | rprocess specification |
gompertz | Gompertz model with log-normal observations. |
hitch | Hitching C snippets and R functions to pomp_fun objects |
inv_log_barycentric | Transformations |
kalman | Ensemble Kalman filters |
kalmanFilter | Kalman filter |
logit | Transformations |
logLik | Log likelihood |
logLik-method | Log likelihood |
logmeanexp | The log-mean-exp trick |
log_barycentric | Transformations |
LondonYorke | Historical childhood disease incidence data |
lookup | Lookup table |
map | skeleton specification |
mcap | Monte Carlo adjusted profile |
melt | Melt |
melt-method | Melt |
mif2 | Iterated filtering: maximum likelihood by iterated, perturbed Bayes maps |
mif2-method | Iterated filtering: maximum likelihood by iterated, perturbed Bayes maps |
mvn_diag_rw | MCMC proposal distributions |
mvn_rw | MCMC proposal distributions |
mvn_rw_adaptive | MCMC proposal distributions |
nlf | Nonlinear forecasting |
nlf_objfun | Nonlinear forecasting |
nlf_objfun-method | Nonlinear forecasting |
obs | obs |
obs-method | obs |
onestep | rprocess specification |
ou2 | Two-dimensional discrete-time Ornstein-Uhlenbeck process |
parameter_trans | parameter transformations |
parameter_trans-method | parameter transformations |
parmat | Create a matrix of parameters |
parmat-method | Create a matrix of parameters |
partrans | partrans workhorse |
partrans-method | partrans workhorse |
parus | Parus major population dynamics |
periodic_bspline_basis | B-spline bases |
pfilter | Particle filter |
pfilter-method | Particle filter |
plot | pomp plotting facilities |
plot-method | pomp plotting facilities |
pmcmc | The particle Markov chain Metropolis-Hastings algorithm |
pmcmc-method | The particle Markov chain Metropolis-Hastings algorithm |
pomp | Constructor of the basic pomp object |
pomp,package | Inference for partially observed Markov processes |
pomp_constructor | Constructor of the basic pomp object |
pomp_examples | pre-built pomp examples |
pred_mean | Prediction mean |
pred_mean-method | Prediction mean |
pred_var | Prediction variance |
pred_var-method | Prediction variance |
priors | prior specification |
prior_spec | prior specification |
probe | Probes (AKA summary statistics) |
probe-method | Probes (AKA summary statistics) |
probe_acf | Useful probes for partially-observed Markov processes |
probe_ccf | Useful probes for partially-observed Markov processes |
probe_marginal | Useful probes for partially-observed Markov processes |
probe_match | Probe matching |
probe_mean | Useful probes for partially-observed Markov processes |
probe_median | Useful probes for partially-observed Markov processes |
probe_nlar | Useful probes for partially-observed Markov processes |
probe_objfun | Probe matching |
probe_objfun-method | Probe matching |
probe_period | Useful probes for partially-observed Markov processes |
probe_quantile | Useful probes for partially-observed Markov processes |
probe_sd | Useful probes for partially-observed Markov processes |
probe_var | Useful probes for partially-observed Markov processes |
profile_design | Design matrices for pomp calculations |
proposals | MCMC proposal distributions |
rbetabinom | Beta-binomial distribution |
repair_lookup_table | Covariates |
reproducibility_tools | Tools for reproducible computations |
reulermultinom | Eulermultinomial and gamma-whitenoise distributions |
rgammawn | Eulermultinomial and gamma-whitenoise distributions |
ricker | Ricker model with Poisson observations. |
rinit | rinit workhorse |
rinit-method | rinit workhorse |
rinit_spec | rinit specification |
rmeasure | rmeasure workhorse |
rmeasure-method | rmeasure workhorse |
rmeasure_spec | rmeasure specification |
rprior | rprior workhorse |
rprior-method | rprior workhorse |
rprocess | rprocess workhorse |
rprocess-method | rprocess workhorse |
rprocess_spec | rprocess specification |
runif_design | Design matrices for pomp calculations |
rw2 | Two-dimensional random-walk process |
rw_sd | rw_sd |
sannbox | Simulated annealing with box constraints. |
saved_states | Saved states |
saved_states-method | Saved states |
simulate | Simulations of a partially-observed Markov process |
simulate-method | Simulations of a partially-observed Markov process |
sir | Compartmental epidemiological models |
sir2 | Compartmental epidemiological models |
SIR_models | Compartmental epidemiological models |
skeleton | skeleton workhorse |
skeleton-method | skeleton workhorse |
skeleton_spec | skeleton specification |
slice_design | Design matrices for pomp calculations |
sobol_design | Design matrices for pomp calculations |
spect | Power spectrum |
spect-method | Power spectrum |
spect_match | Spectrum matching |
spect_objfun | Spectrum matching |
spect_objfun-method | Spectrum matching |
spy | Spy |
spy-method | Spy |
states | Latent states |
states-method | Latent states |
stew | Tools for reproducible computations |
summary | Summary methods |
summary-method | Summary methods |
time | Methods to extract and manipulate the obseration times |
time-method | Methods to extract and manipulate the obseration times |
time<- | Methods to extract and manipulate the obseration times |
time<--method | Methods to extract and manipulate the obseration times |
timezero | The zero time |
timezero-method | The zero time |
timezero<- | The zero time |
timezero<--method | The zero time |
traces | Traces |
traces-method | Traces |
trajectory | Trajectory of a deterministic model |
trajectory-method | Trajectory of a deterministic model |
traj_match | Trajectory matching |
traj_objfun | Trajectory matching |
traj_objfun-method | Trajectory matching |
transformations | Transformations |
userdata | Facilities for making additional information to basic components |
vectorfield | skeleton specification |
verhulst | Verhulst-Pearl model |
vmeasure | vmeasure workhorse |
vmeasure-method | vmeasure workhorse |
vmeasure_spec | vmeasure specification |
window | Window |
window-method | Window |
workhorses | Workhorse functions for the 'pomp' algorithms. |
wpfilter | Weighted particle filter |
wpfilter-method | Weighted particle filter |
wquant | Weighted quantile function |