fit_progression_rate_model: Fit a progression rate model to case-carrier data

In nickjcroucher/progressionEstimation: R package for the estimation of microbial progression rates

Fit a progression rate model to case-carrier data

Description

Fit a progression rate model to case-carrier data

Usage

fit_progression_rate_model(
  input_data,
  type_specific = TRUE,
  location_adjustment = TRUE,
  stat_model = "poisson",
  strain_as_primary_type = FALSE,
  strain_as_secondary_type = FALSE,
  model_description = NULL,
  num_chains = 4,
  num_iter = 10000,
  num_cores = 1,
  adapt_delta_value = 0.8,
  stepsize_value = 1,
  max_treedepth_value = 10
)

Arguments

input_data	List of lists generated by 'process_input_data'
type_specific	Boolean specifying whether progression rates vary between types
location_adjustment	Boolean specifying whether progression rates vary between locations
stat_model	Whether progression to disease is "poisson" (Poisson process) or "negbin" (overdispersed negative binomial distribution)
strain_as_primary_type	Whether strain should be used as the primary determinant of progression rate, and the other type used as the secondary determinant
strain_as_secondary_type	Whether strain should be used as the secondary determinant of progression rate, and the other type used as the primary determinant
model_description	Descriptive title of model
num_chains	Number of MCMCs to be run for inference
num_iter	Length of MCMCs
num_cores	Number of threads used to calculate MCMCs
adapt_delta_value	Target average acceptance probability of MCMCs (default = 0.8)
stepsize_value	Initial MCMC step size (default = 1)
max_treedepth_value	Depth of tree explored by MCMC sampler (default = 10)

Value

A stanfit object

nickjcroucher/progressionEstimation documentation built on April 15, 2023, 3:53 p.m.