ozab: Fit OZAB Model

In EriqLaplus/OZAB: Implemtation of Ordinal Zero-Augmented Beta Models in Stan

Description

Fit OZAB Model

Usage

ozab(
  df,
  presence_formula,
  abundance_formula,
  cutpoint_scheme,
  link_function = "logit",
  ...,
  prior_presence_mean = 0,
  prior_abundance_mean = 0,
  prior_presence_var = 10,
  prior_abundance_var = 10
)

Arguments

df	Tibble containing Species, Cover Class, and Covariates
presence_formula	Formula for Specifying Presence / Absence
abundance_formula	Formula for Specifying Abundance
cutpoint_scheme	Vector of Cutpoint Scheme Used
link_function	Link Function to Use; Options are logit and probit; Defaults to logit
...	Additional Parameters to be Passed to Stan
prior_presence_mean	A vector of mean values for prior presence coefficients
prior_abundance_mean	A vector of mean values for prior abundance coefficients
prior_presence_var	A vector of variance values for prior presence coefficients
prior_abundance_var	A vector of variance values for prior abundance coefficients

Value

Stan Object Fit

Examples

## Not run: 
  sagebrush2 <-
sagebrush %>%
 filter(Species == 'Artemisia tridentata') %>%
 add_presence(cover_class_col = `Cover Class`) %>%
 mutate(
   `Dist. to Bound` = `Dist. to Bound` / 1000,
   Topography2 = Topography^2
 )
ozab(
 presence_formula = Presence ~ Topography + Fire + `Dist. to Bound`,
 abundance_formula = `Cover Class` ~ Topography + Topography2 + Fire,
 cutpoint_scheme = daubenmire(),
 chains = 1
)

## End(Not run)

EriqLaplus/OZAB documentation built on March 31, 2021, 4:35 a.m.