fixing cran problems

DESCRIPTION

@@ -12,7 +12,10 @@ Authors@R: c(person("Josh", "Yamamoto", role = c("aut", "cre"),
              person("Kate", "Hu", role = "aut"))
 Maintainer: Josh Yamamoto <joshuayamamoto5@gmail.com>
 Description: Simplifies the process of fitting a zero-inflated estimator
-    onto a dataset. 
+    onto a dataset. This estimator is a combination of a linear mixed effects regression model 
+    and a logistic mixed effects regression model which is summarized by White et al (2024, <arXiv:2402.03263>).
+    The variance is estimated through a parametric bootstrapping method which is given 
+    by Chandra et al (2012, <doi:10.1080/03610918.2011.598991>). 
 License: CC0
 Encoding: UTF-8
 LazyData: true

R/saeczi.R

@@ -17,9 +17,39 @@
 #'
 #' @details The arguments `lin_formula`, and `log_formula`
 #' can be unquoted or quoted. The function can handle both forms.
-#'
+#' 
 #' The two datasets (pop_dat and samp_dat) must have the same column names for the domain level,
 #' as well as the predictor variables for the function to work.
+#' 
+#' @returns 
+#' An object of class `zi_mod` with defined `print()` and `summary()` methods. 
+#' The object is structured like a list and contains the following elements:
+#' 
+#' * call: The original function call
+#' 
+#' * res: A data.frame containing the estimates and mse estimates
+#' 
+#' * bootstrap_log: A list containing any messages and warnings that occur during the bootstrap process
+#' 
+#' * lin_mod: The modeling object used to fit the original linear model
+#' 
+#' * log_mod: The modeling object used to fit the original logistic model
+#' 
+#' @examples 
+#' data(pop)
+#' data(samp)
+#' 
+#' lin_formula <- DRYBIO_AG_TPA_live_ADJ ~ tcc16 + elev
+#' 
+#' result <- saeczi(samp,
+#'                  pop, 
+#'                  lin_formula,
+#'                  log_formula = lin_formula,
+#'                  domain_level = "COUNTYFIPS",
+#'                  mse_est = TRUE,
+#'                  B = 5,
+#'                  parallel = FALSE)
+#'
 #' @export saeczi
 #' @import stats
 #' @importFrom progressr progressor with_progress
@@ -266,7 +296,7 @@ saeczi <- function(samp_dat,
       }) 
 
     } else {
-
+      
       res <- 
         purrr::map(.x = boot_samp_ls,
                    .f = \(.x) { 
@@ -279,7 +309,7 @@ saeczi <- function(samp_dat,
                      type = "iterator",
                      clear = TRUE
                    ))
-
+      
       beta_lm_mat <- res |>
         map_dfr(.f = ~ .x$params$beta_lm) |>
         as.matrix()
@@ -342,7 +372,7 @@ saeczi <- function(samp_dat,
     bootstrap_log <- NA
 
   }
-
+  
 
   out <- list(
     call = funcCall,