Separate local from global parameters.

* Move altering, monotonicity and other to xs_opts and xf_opts * Add more formula tools * Renaming functions
ModelOriented · Nov 30, 2018 · c43673c · c43673c
1 parent 520263c
commit c43673c
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Showing 40 changed files with 1,319 additions and 817 deletions.
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -21,5 +21,6 @@ Suggests:
     factoMerger,
     testthat,
     knitr,
-    rmarkdown
+    rmarkdown,
+    ResourceSelection
 VignetteBuilder: knitr
diff --git a/NAMESPACE b/NAMESPACE
@@ -1,22 +1,16 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(extract_xspliner_function,xspliner)
 S3method(plot,xspliner)
 S3method(predict,xspliner)
 S3method(xspline,default)
 S3method(xspline,explainer)
 S3method(xspline,formula)
-export(extract_formula_var_names)
-export(factor_opts_default)
-export(get_component_params)
-export(get_formula_details)
-export(get_formula_raw_components)
-export(get_formula_special)
-export(get_special_component_details)
-export(get_special_components_info)
-export(numeric_opts_default)
-export(prepare_call)
-export(r_squared)
-export(transform_formula_chr)
-export(transformed_formula_object)
+export(aic)
+export(extract_xspliner_function)
+export(get_special_predictors)
+export(hoslem)
+export(xf_opts_default)
+export(xs_opts_default)
 export(xspline)
 importFrom(magrittr,"%>%")
diff --git a/R/plot-xspliner.R b/R/plot-xspliner.R
@@ -25,7 +25,7 @@ plot.xspliner <- function(x, variable_name = NULL, plot_response = TRUE,
     }
 
     response_var <- environment(x)$response
-    xp_call <- environment(x)$xs_call[[variable_name]]
+    xp_call <- environment(x)$xs_functions[[variable_name]]
 
     if (plot_data) {
       plot_range <- range(data[, variable_name])
@@ -35,7 +35,7 @@ plot.xspliner <- function(x, variable_name = NULL, plot_response = TRUE,
 
     plot_data_data <- data
 
-    plot_response_data <- environment(x)$xs_env_list[[variable_name]]$blackbox_response_obj
+    plot_response_data <- environment(x)$quantitative_transitions[[variable_name]]$effect_outcome
     colnames(plot_response_data) <- c(variable_name, response_var)
 
     x_approx <- seq(plot_range[1], plot_range[2], length.out = nrow(plot_response_data))

diff --git a/R/predict-xspliner.R b/R/predict-xspliner.R
@@ -5,5 +5,5 @@
 #'
 #' @export
 predict.xspliner <- function(xspliner, newdata) {
-  mgcv::predict.gam(xspliner, newdata = newdata)
+  stats::predict.glm(xspliner, newdata = newdata)
 }