Man pages for ben18785/incidenceinflation
Estimate R0 Given Case Reporting Delays
| accept_reject | Performs Metropolis accept-reject step |
| combine_chains | Combines Markov chains across multiple runs of mcmc_single |
| conditional_cases_logp | Calculates (unnormalised) log-probability of a true case... |
| construct_w_matrix | Constructs a matrix of w vectors |
| convert_df_to_posterior_format | Converts a single tibble to posterior format |
| convert_results_to_posterior_format | Converts results to format required for posterior package |
| create_reporting_from_single_parameters_df | Creates a reporting parameter tibble with a single set of... |
| detected_after_unobserved_prob | Probability a case is detected by a later time given it was... |
| dgamma_mean_sd | Reparameterisation of gamma pdf using mean and sd |
| expected_cases | Gives cases expected given history of cases and Rt |
| gamma_discrete_pmf | Discrete gamma probability mass function |
| generate_snapshots | Generates case data with snapshots of reported cases at each... |
| ILI_2014 | Influenza-like illness (ILI) in US from 2014-2015 |
| maximise_reporting_logp | Select reporting parameters by maximising log-probability |
| max_uncertain_days | Calculates max number of days we are uncertain about... |
| mcmc | Runs MCMC or optimisation to estimate Rt, cases and reporting... |
| mcmc_single | Runs MCMC or optimisation to estimate Rt, cases and reporting... |
| measles_NL_2013 | Measles outbreak data in Netherlands from 2013-2014 |
| metropolis_step | Sample reporting parameters using a single Metropolis step |
| metropolis_step_overdispersion | Performs a single Metropolis step to update overdispersion... |
| metropolis_steps | Sample reporting parameters using Metropolis MCMC |
| nb_log_likelihood_Rt_piece | Calculates negative-binomial log-likelhood within a single Rt... |
| observation_process_all_times_logp | Observation probability across all onset times |
| observation_process_logp | Calculates observation process log probability density |
| observation_process_single_logp | Calculates observation process log probability density for a... |
| observed_cases | Generate reported case trajectories for each day when cases... |
| observed_cases_single | Cases arising on a given day which are reported between two... |
| observed_cases_trajectory | Generate trajectory of reported cases for a given count... |
| pgamma_mean_sd | Reparameterisation of gamma cdf using mean and sd |
| prior_reporting_parameters | Gamma prior for reporting parameters |
| propose_overdispersion_parameter | Propose new overdispersion parameter by sampling from a... |
| propose_reporting_parameters | Propose new reporting parameters using normal kernel centered... |
| qgamma_mean_sd | Reparameterisation of gamma inverse-cdf using mean and sd |
| sample_cases_history | Draws a possible history (or histories) of cases |
| sample_nb_Rt_piece | Uses importance resampling to infer a posterior over Rt under... |
| sample_or_maximise_gamma | Draws from the gamma distribution or returns the value which... |
| sample_reporting | Draw reporting parameter values either by sampling or by... |
| sample_Rt | Sample piecewise-constant Rt values |
| sample_Rt_single_piece | Sample a single Rt value corresponding to a single piecewise-... |
| sample_true_cases_single_onset | Samples a case count arising on a given onset day |
| state_process_logp | Determines the probability of a given number of cases given a... |
| state_process_nb_logp_all_onsets | Calculates the overall log-probability of cases conditional... |
| thin_series | Thins cases |
| thin_single_series | Thins cases for a single onset time |
| true_cases | Generate true case series |
| true_cases_single | Generates true cases for a single day |
| undetected_prob | Probability case remains undetected over time |
| weights_series | Generate weights series |
