create_posterior_func: Posterior function pointer

View source: R/posteriors.R

create_posterior_funcR Documentation

Posterior function pointer

Description

Takes all of the input data/parameters and returns a function pointer. This function finds the posterior for a given set of input parameters (theta) and infection histories without needing to pass the data set back and forth. No example is provided for function_type=2, as this should only be called within serosolver

Usage

create_posterior_func(
  par_tab,
  antibody_data,
  antigenic_map = NULL,
  possible_exposure_times = NULL,
  prior_version = 1,
  solve_likelihood = TRUE,
  age_mask = NULL,
  measurement_indices_by_time = NULL,
  n_alive = NULL,
  function_type = 1,
  antibody_level_before_infection = FALSE,
  data_type = 1,
  biomarker_groups_weights = 1,
  verbose = FALSE,
  ...
)

Arguments

par_tab

the parameter table controlling information such as bounds, initial values etc. See example_par_tab

antibody_data

the data frame of data to be fitted. Must have columns: group (index of group); individual (integer ID of individual); samples (numeric time of sample taken); virus (numeric time of when the virus was circulating); biomarker_group (integer of the observation group type, using a unique value for each distinctive type of observation underpinned by the same generative model); titre (integer of titre value against the given virus at that sampling time). See example_antibody_data

antigenic_map

(optional) a data frame of antigenic x and y coordinates. Must have column names: x_coord; y_coord; inf_times. See example_antigenic_map

possible_exposure_times

(optional) if no antigenic map is specified, this argument gives the vector of times at which individuals can be infected

prior_version

which infection history assumption version to use? See describe_priors for options. Can be 1, 2, 3 or 4

solve_likelihood

usually set to TRUE. If FALSE, does not solve the likelihood and instead just samples/solves based on the model prior

age_mask

see create_age_mask - a vector with one entry for each individual specifying the first epoch of circulation in which an individual could have been exposed

measurement_indices_by_time

if not NULL, then use these indices to specify which measurement bias parameter index corresponds to which time

n_alive

if not NULL, uses this as the number alive in a given year rather than calculating from the ages. This is needed if the number of alive individuals is known, but individual birth dates are not

function_type

integer specifying which version of this function to use. Specify 1 to give a posterior solving function; 2 to give the gibbs sampler for infection history proposals; otherwise just solves the titre model and returns predicted titres. NOTE that this is not the same as the attack rate prior argument, version!

data_type

integer, currently accepting 1 for discrete or 2 for continuous.

verbose

if TRUE, prints warning messages

...

other arguments to pass to the posterior solving function

titre_before_infection

TRUE/FALSE value. If TRUE, solves titre predictions, but gives the predicted titre at a given time point BEFORE any infection during that time occurs.

Value

a single function pointer that takes only pars and infection_histories as unnamed arguments. This function goes on to return a vector of posterior values for each individual

Examples

## Not run: 
data(example_par_tab)
data(example_antibody_data)
data(example_antigenic_map)
data(example_inf_hist)

## Simple model solving code. Output matches entries of example_antibody_data
model_func <- create_posterior_func(example_par_tab, example_antibody_data, example_antigenic_map, function_type = 3)
y <- model_func(example_par_tab$values, example_inf_hist)

## Solve likelihood
par_tab <- example_par_tab[example_par_tab$names != "phi",]
likelihood_func <- create_posterior_func(par_tab, example_antibody_data, example_antigenic_map, function_type = 1, prior_version = 2)
liks <- likelihood_func(par_tab$values, example_inf_hist)

## End(Not run)

seroanalytics/serosolver documentation built on March 21, 2024, 5:38 a.m.