Function reference • serosim

All functions
`antibody_model_biphasic()`	Biphasic antibody boosting-waning model
`antibody_model_biphasic_cpp()`	Biphasic antibody boosting-waning model Rcpp implementation
`antibody_model_biphasic_cross_reactivity()`	Biphasic antibody boosting-waning model with cross-reactive strains
`antibody_model_monophasic()`	Monophasic antibody boosting-waning model
`antibody_model_monophasic_cpp()`	Monophasic antibody boosting-waning model Rcpp implementation
`antibody_model_monophasic_cross_reactivity()`	Monophasic antibody boosting-waning model with cross-reactive strains
`antibody_model_typhoid()`	Power law antibody boosting and waning
`biomarker_protection()`	Function to calculate the risk of infection at a given biomarker quantity
`convert_indices_matrix_to_vector()`	Convert 2D indexing to 1D indexing
`draw_parameters_fixed_fx()`	Draw parameters with fixed effects
`draw_parameters_fixed_fx_biomarker_dep()`	Draw parameters fixed effects with biomarker-quantity-dependent boosting
`draw_parameters_random_fx()`	Draw parameters with random effects
`draw_parameters_random_fx_biomarker_dep()`	Draw parameters random effects with biomarker-quantity-dependent boosting
`example_biomarker_map`	Example biomarker map
`example_biomarker_map_numeric`	Example numeric biomarker map
`example_biomarker_states`	Example biomarker states
`example_biomarker_states_wide`	Example biomarker states (wide)
`example_demography`	Example demography tibble
`example_exposure_force`	Example force of exposure
`example_exposure_probabilities`	Example exposure probability
`example_foe_pars`	Example force of exposure parameters (`foe_pars`)
`example_immune_histories`	Example imune histories
`example_immune_histories_wide`	Example immune histories (wide)
`example_model_pars`	Example model parameters (`model_pars`)
`example_model_pars_biphasic`	Example model parameters for biphasic waning model
`example_model_pars_numeric`	Example numeric model parameters (`model_pars`)
`example_model_pars_typhoid`	Example model parameters for typhoid model (`model_pars_typhoid`)
`example_observed_biomarker_states`	Example observed biomarker states
`exposure_model_dem_mod()`	Exposure Model Modified By Relevant Demographic Elements
`exposure_model_fixed()`	Fixed probability of exposure
`exposure_model_gaussian_process()`	Gaussian process model
`exposure_model_indiv_fixed()`	Known individual-level probability of exposure
`exposure_model_simple_FOE()`	Exposure Model Simple- Force of Exposure (FOE)
`exposure_model_sir()`	SIR Exposure Model
`generate_pop_demography()`	Generate population demography dataset
`immunity_model_all_successful()`	Null immunity model
`immunity_model_ifxn_biomarker_prot()`	Immunity model for infection with biomarker-quantity-mediated protection
`immunity_model_vacc_ifxn_biomarker_prot()`	Immunity model for vaccination and infection events with biomarker-quantity-mediated protection
`immunity_model_vacc_ifxn_simple()`	Simple immunity model for vaccination and infection events
`immunity_model_vacc_only()`	Vaccine-mediated immunity model
`normal_to_lognormal_mean()`	Convert normal distributions to log-normal distributions and return mean
`normal_to_lognormal_sd()`	Convert normal distributions to log-normal distributions and return standard deviation
`observation_model_continuous()`	Observation model for continuous assays with no added noise
`observation_model_continuous_bounded()`	Observation model for continuous assays with detection limits and no added noise
`observation_model_continuous_bounded_noise()`	Observation model for continuous assays with detection limits and added noise
`observation_model_continuous_noise()`	Observation model for continuous assays with no detection limits and added noise
`observation_model_discrete()`	Observation model for discrete assays with no added noise
`observation_model_discrete_noise()`	Observation Model For Discrete Assays With Added Noise
`plot_antibody_model()`	Plots example trajectories of the provided antibody kinetics model
`plot_biomarker_dependent_boosting()`	Generate a plot displaying proportion of full boost received at each starting biomarker quantity
`plot_biomarker_mediated_protection()`	Plot biomarker mediated protection graphs for each pathogen
`plot_biomarker_quantity()`	Plot biomarker quantities across time for all individuals and biomarkers
`plot_exposure_force()`	Plot individual exposure probabilities across time for all individuals and exposure events
`plot_exposure_model()`	Plots the probability of exposure over time for the provided exposure models
`plot_exposure_prob()`	Plot probability of a successful exposure event for all individuals and exposure events
`plot_immune_histories()`	Plot individual immune histories
`plot_obs_biomarkers_one_sample()`	Plot Observed Biomarker Quantities For One Observation Time
`plot_obs_biomarkers_paired_sample()`	Plot biomarker quantities for multiple observation times and paired samples
`plot_subset_individuals_history()`	Plot biomarker states and immune histories for a subset of individuals
`precomputation_checks()`	Pre-compute exposure probabilities
`reformat_biomarker_map()`	Reformat `biomarker_map` or `model_pars` exposure and biomarker variables
`runserosim()`	Main simulation function for serosim
`simulate_birth_times()`	Simulate random birth times
`simulate_gaussian_process()`	Simulate incidence curve using Gaussian Process
`simulate_removal_times()`	Simulate removal times for individuals
`update()`	runserosim function update message

Reference

All functions