fit | R Documentation |
Function to estimate a Bayesian case-control model.
fit(
data = data_sim,
contamination = F,
show_code = T,
offset = F,
beta_prior = "normal",
small_area_prior = "fixed",
large_area_prior = NA,
intercept_scale = NA,
iter = 100,
warmup = 50,
thin = 4,
cores = 4,
chains = 4,
control = list(max_treedepth = 7, adapt_delta = 0.8),
verbose = TRUE
)
data |
list, survey and shapefile combined list object created with the |
contamination |
logical, should the model include the Rota et al. (2013) style contamination layer? Defaults to |
show_code |
logical, should the stan code print on the screen at the end of the run? Defaults to |
offset |
logical, should the model include a King and Zeng (2001) style offset ? if contamination is also specified, this will be a contaminated-offset. Defaults to |
beta_prior |
string, what prior should the regression coefficients have? Choice between: "normal" and "cauchy." |
small_area_prior |
string, what should be the small-area effects type? Choice between: "fixed," "random," "ICAR," and "BYM2." Specify |
large_area_prior |
string, what should be the large-area effects type? Choice between: "fixed" and "random." Specify |
intercept_scale |
integer, scale of intercept; see |
iter |
integer, number of draws; see |
warmup |
number of warmup draws; see |
thin |
integer, number to thin draws; see |
cores |
integer, number of cores to use; see |
chains |
integer, number of chains; see |
control |
list; tree depth and adapt delta; see |
verbose |
logical, print full stan output? Defaults to |
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