This is the output of the following estimator, and is here to speed up some examples:
Usage
data(england_covid_poisson)Format
A dataframe containing the following columns:
time (as.time_period) - the time column
incidence.fit (numeric) - the incidence.fit column
incidence.se.fit (numeric) - the incidence.se.fit column
incidence.0.025 (numeric) - the incidence.0.025 column
incidence.0.05 (numeric) - the incidence.0.05 column
incidence.0.25 (numeric) - the incidence.0.25 column
incidence.0.5 (numeric) - the incidence.0.5 column
incidence.0.75 (numeric) - the incidence.0.75 column
incidence.0.95 (numeric) - the incidence.0.95 column
incidence.0.975 (numeric) - the incidence.0.975 column
growth.fit (numeric) - the growth.fit column
growth.se.fit (numeric) - the growth.se.fit column
growth.0.025 (numeric) - the growth.0.025 column
growth.0.05 (numeric) - the growth.0.05 column
growth.0.25 (numeric) - the growth.0.25 column
growth.0.5 (numeric) - the growth.0.5 column
growth.0.75 (numeric) - the growth.0.75 column
growth.0.95 (numeric) - the growth.0.95 column
growth.0.975 (numeric) - the growth.0.975 column
Any grouping allowed.
1410 rows and 19 columns
Details
england_covid %>% time_aggregate() %>% ggoutbreak::poisson_locfit_model(window=14)