state_process_nb_logp_all_onsets: Calculates the overall log-probability of cases conditional...
In ben18785/incidenceinflation: Estimate R0 Given Case Reporting Delays
View source: R/probabilities.R
state_process_nb_logp_all_onsets R Documentation
Calculates the overall log-probability of cases conditional on their history
and Rt values, assuming a negative-binomial renewal model
Description
Specifically, this assumes the probability is of the form:
\prod_tau=1^T NB(cases_true_tau|Rt * \sum_s=1^tau-1 w_s cases_true_tau-s, kappa)
Usage
state_process_nb_logp_all_onsets(kappa, cases_history_rt_df, serial_parameters)
Arguments
kappa
an overdispersion parameter value (if <= 0, returns -Inf)
cases_history_rt_df
a tibble with three columns: 'time_onset',
'cases_true' and 'Rt'
serial_parameters
named list of 'mean' and 'sd' of gamma distribution
characterising the serial interval distribution
Value
a log-probability value
ben18785/incidenceinflation documentation built on Feb. 8, 2024, 2:36 a.m.
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View source: R/probabilities.R
| state_process_nb_logp_all_onsets | R Documentation |
Calculates the overall log-probability of cases conditional on their history and Rt values, assuming a negative-binomial renewal model
Description
Specifically, this assumes the probability is of the form:
\prod_tau=1^T NB(cases_true_tau|Rt * \sum_s=1^tau-1 w_s cases_true_tau-s, kappa)
Usage
state_process_nb_logp_all_onsets(kappa, cases_history_rt_df, serial_parameters)
Arguments
kappa |
an overdispersion parameter value (if <= 0, returns -Inf) |
cases_history_rt_df |
a tibble with three columns: 'time_onset', 'cases_true' and 'Rt' |
serial_parameters |
named list of 'mean' and 'sd' of gamma distribution characterising the serial interval distribution |
Value
a log-probability value
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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