Package: nfidd 1.0.0

NFIDD course contributors

nfidd: Material to support course on nowcasting and forecasting of infectious disease dynamics

Resources to support a short course on nowcasting and forecasting of infectious disease dynamics.

Authors:NFIDD course contributors [cre, aut]

# Install 'nfidd' in R:

install.packages('nfidd', repos = c('https://epiforecasts.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

infection_times - Infection times
mech_forecasts - Forecasts from a mechanistic model
rw_forecasts - Forecasts from a semi-mechanistic model
stat_forecasts - Forecasts from a semi-mechanistic model with additional statistical complexity

On CRAN:

Last updated 17 days agofrom:d01678e108 (on v1.0.0). Checks:OK: 3 NOTE: 4. Indexed: no.

Help page	Topics
Simulate symptom onset and hospitalization times from infection times	add_delays
Discretise a Continuous Delay Distribution	censored_delay_pmf
Convolve a Time Series with a Delay Distribution	convolve_with_delay
Geometric Differenced Autoregressive Process	geometric_diff_ar
Geometric Random Walk	geometric_random_walk
Infection times	infection_times
Convert infection times to a daily time series	make_daily_infections
Generate a probability mass function for the generation time	make_gen_time_pmf
Generate a probability mass function for the incubation period	make_ip_pmf
Forecasts from a mechanistic model	mech_forecasts
Create a CmdStanModel with NFIDD Stan functions	nfidd_cmdstan_model
Load Stan functions as a string	nfidd_load_stan_functions
Get Stan files containing specified functions	nfidd_stan_function_files
Get Stan function names from Stan files	nfidd_stan_functions
List Available Stan Models in NFIDD	nfidd_stan_models
Get the path to Stan code	nfidd_stan_path
Simulate Infections using the Renewal Equation	renewal
Forecasts from a semi-mechanistic model	rw_forecasts
Simulate symptom onsets from daily infection counts	simulate_onsets
Forecasts from a semi-mechanistic model with additional statistical complexity	stat_forecasts