Revised description as requested by CRAN team.

DESCRIPTION

@@ -5,7 +5,7 @@ Authors@R:
     person("Chitu", "Okoli", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "https://orcid.org/0000-0001-5574-7572"))
 Language: en-US
-Description: This is a wrapper package for `mgcv` that makes it easier to create high-performing Generalized Additive Models (GAMs). With its central function autogam, by entering just a dataset and the name of the outcome column as inputs, AutoGAM tries to automate as much as possible the procedure of configuring a highly accurate GAM at reasonably high speed, even for large datasets.
+Description: This wrapper package for 'mgcv' makes it easier to create high-performing Generalized Additive Models (GAMs). With its central function autogam(), by entering just a dataset and the name of the outcome column as inputs, 'AutoGAM' tries to automate the procedure of configuring a highly accurate GAM which performs at reasonably high speed, even for large datasets.
 License: MIT + file LICENSE
 Suggests: 
     testthat (>= 3.0.0)

R/autogam.R

@@ -1,6 +1,7 @@
 #' Automate the creation of a Generalized Additive Model (GAM)
 #'
-#' This is a wrapper package for `mgcv` that makes it easier to create high-performing Generalized Additive Models (GAMs). By entering just a dataset and the name of the outcome column as inputs, `autogam()` tries to automate as much as possible the procedure of configuring a highly accurate GAM at reasonably high speed, even for large datasets.
+#' `autogam()` is a wrapper for 'mgcv::gam()' that makes it easier to create high-performing Generalized Additive Models (GAMs). By entering just a dataset and the name of the outcome column as inputs, `autogam()` tries to automate the procedure of configuring a highly accurate GAM which performs at reasonably high speed, even for large datasets.
+#'
 #'
 #' @export
 #'