Merge pull request #95 from rsquaredacademy/develop

Internal changes

Author: aravindhebbali

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: blorr
 Type: Package
 Title: Tools for Developing Binary Logistic Regression Models
-Version: 0.2.1.9000
+Version: 0.2.2
 Authors@R: person("Aravind", "Hebbali", email = "hebbali.aravind@gmail.com", role = c("aut", "cre"), 
     comment = c(ORCID = "0000-0001-9220-9669"))
 Description: Tools designed to make it easier for beginner and intermediate users to build and validate 
@@ -20,33 +20,23 @@ Imports:
     dplyr,
     e1071,  
     ggplot2,
-    glue,
     gridExtra,
     magrittr,
     purrr,
     Rcpp,
     rlang,
     scales,
-    shiny,
     stats,
     tibble,
-    utils
+    utils,
+    xplorerr
 Suggests: 
     covr,
-    descriptr,
     grid,
     ineq,
-    jsonlite, 
-    lubridate,
     knitr,
-    readr,
-    readxl,
     rmarkdown,
-    shinyBS,
-    shinythemes,
-    stringr,
     testthat,
-    tidyr,
     vdiffr
 License: MIT + file LICENSE
 URL: URL: https://blorr.rsquaredacademy.com/, https://github.com/rsquaredacademy/blorr

NAMESPACE

@@ -166,7 +166,6 @@ importFrom(ggplot2,xlab)
 importFrom(ggplot2,xlim)
 importFrom(ggplot2,ylab)
 importFrom(ggplot2,ylim)
-importFrom(glue,glue)
 importFrom(gridExtra,grid.arrange)
 importFrom(gridExtra,marrangeGrob)
 importFrom(magrittr,"%<>%")

NEWS.md

@@ -1,3 +1,7 @@
+# blorr 0.2.2
+
+This is a patch release to fix CRAN errors.
+
 # blorr 0.2.1
 
 This is a patch release to fix bugs in the app.
@@ -22,4 +26,4 @@ choice ([#64](https://github.com/rsquaredacademy/blorr/issues/64))
 
 # blorr 0.1.0
 
-Initial release
+Initial release

R/blr-launch-app.R

@@ -19,8 +19,8 @@ blr_launch_app <- function() {
 	check_suggests('shinythemes')
 	check_suggests('stringr')
 	check_suggests('tidyr')
-	
-	shiny::runApp(appDir = system.file("application", package = "blorr"))
+
+	xplorerr::app_logistic_regression()
 
 }
- 
+

R/blr-lorenz-curve.R

@@ -109,7 +109,7 @@ blr_lorenz_curve <- function(model, data = NULL, title = "Lorenz Curve",
     geom_line(aes(x = `cum_1s_per`, y = `cum_0s_per`),
                 color = lorenz_curve_col) +
     geom_line(aes(x = `cum_1s_per`, y = `cum_1s_per`), color = diag_line_col) +
-    ggtitle(label = title, subtitle = glue("Gini Index = ", {g_index})) +
+    ggtitle(label = title, subtitle = paste0("Gini Index = ", g_index)) +
     xlab(xaxis_title) + ylab(yaxis_title) +
     theme(plot.title = element_text(hjust = 0.5),
           plot.subtitle = element_text(hjust = 0.5))

R/blr-lrtest.R

@@ -81,10 +81,10 @@ lr_reduced_model <- function(full_model) {
 
   dat <-
     full_model %>%
-    use_series(data) 
+    use_series(data)
 
 
-  glm(glue(dep, " ~ 1"), data = dat, family = binomial(link = "logit"))
+  glm(paste0(dep, " ~ 1"), data = dat, family = binomial(link = "logit"))
 
 }
 

R/blr-output.R

@@ -230,12 +230,12 @@ print_model_fit_stats <- function(x) {
   cat(fc("Model Fit Statistics", w), "\n")
   cat(rep("-", w), sep = "", "\n")
   col1names <- c(
-    "Log-Lik Intercept Only:", glue("Deviance(", x$dev_df, "):"), "",
+    "Log-Lik Intercept Only:", paste0("Deviance(", x$dev_df, "):"), "",
     "MCFadden's R2", "ML (Cox-Snell) R2:",
     "McKelvey & Zavoina's R2:", "Count R2:", "BIC:"
   )
   col3names <- c(
-    "Log-Lik Full Model:", glue("LR(", x$lr_df, "):"), "Prob > LR:",
+    "Log-Lik Full Model:", paste0("LR(", x$lr_df, "):"), "Prob > LR:",
     "McFadden's Adj R2:", "Cragg-Uhler(Nagelkerke) R2:",
     "Efron's R2:", "Adj Count R2:", "AIC:"
   )

R/blr-stepwise-backward-regression.R

@@ -135,7 +135,7 @@ blr_step_p_backward.default <- function(model, prem = 0.3, details = FALSE, ...)
       } else {
         end <- TRUE
         cat("\n")
-        cat(crayon::bold$red(glue("No more variables satisfy the condition of p value = {prem}")))
+        cat(crayon::bold$red(paste0("No more variables satisfy the condition of p value = ", prem)))
         cat("\n")
       }
     )
@@ -163,7 +163,7 @@ blr_step_p_backward.default <- function(model, prem = 0.3, details = FALSE, ...)
   )
   print(fi)
 
-  final_model <- glm(paste(response, "~", paste(preds, collapse = " + ")), 
+  final_model <- glm(paste(response, "~", paste(preds, collapse = " + ")),
     data = l, family = binomial(link = 'logit'))
 
   out <- list(removed    = rpred,

R/blr-stepwise-regression.R

@@ -89,7 +89,7 @@ blr_step_p_both.default <- function(model, pent = 0.1, prem = 0.3, details = FAL
   pvals   <- c()
   tvals   <- c()
   step    <- 1
-  ppos    <- step 
+  ppos    <- step
   aic     <- c()
   bic     <- c()
   dev     <- c()
@@ -255,8 +255,8 @@ blr_step_p_both.default <- function(model, pent = 0.1, prem = 0.3, details = FAL
       #   cat("\n\n")
       # }
 
-      m2     <- glm(paste(response, "~", paste(preds, collapse = " + ")), l, 
-                  family = binomial(link = 'logit')) 
+      m2     <- glm(paste(response, "~", paste(preds, collapse = " + ")), l,
+                  family = binomial(link = 'logit'))
       m_sum <- Anova(m2, test.statistic = "Wald")
       pvals_r <- m_sum$`Pr(>Chisq)`
       # tvals_r <- m_sum$Chisq[ppos]
@@ -310,7 +310,7 @@ blr_step_p_both.default <- function(model, pent = 0.1, prem = 0.3, details = FAL
       }
     } else {
       cat("\n")
-      cat(crayon::bold$red(glue("No more variables to be added/removed.")))
+      cat(crayon::bold$red(paste0("No more variables to be added/removed.")))
       cat("\n")
       break
     }
@@ -326,7 +326,7 @@ blr_step_p_both.default <- function(model, pent = 0.1, prem = 0.3, details = FAL
   )
   print(fi)
 
-  final_model <- glm(paste(response, "~", paste(preds, collapse = " + ")), 
+  final_model <- glm(paste(response, "~", paste(preds, collapse = " + ")),
     data = l, family = binomial(link = 'logit'))
 
   out <- list(

R/blr-utils.R

@@ -2,7 +2,6 @@
 #' @importFrom dplyr mutate if_else pull slice
 #' @importFrom tibble tibble as_tibble
 #' @importFrom rlang sym eval_tidy !!
-#' @importFrom glue glue
 #' @importFrom stats coef confint binomial df.residual glm terms
 #' @importFrom utils data
 response_var <- function(model) {
@@ -186,10 +185,10 @@ i_model <- function(model) {
 
   dat <-
     model %>%
-    use_series(data) 
+    use_series(data)
 
   glm(
-    glue(dep, " ~ 1"), data = dat,
+    paste0(dep, " ~ 1"), data = dat,
     family = binomial(link = "logit")
   )
 
@@ -284,13 +283,13 @@ mod_sel_data <- function(model) {
 
 #' @importFrom utils packageVersion menu install.packages
 check_suggests <- function(pkg) {
-  
+
   pkg_flag <- tryCatch(utils::packageVersion(pkg), error = function(e) NA)
-  
+
   if (is.na(pkg_flag)) {
-    
+
     msg <- message(paste0('\n', pkg, ' must be installed for this functionality.'))
-    
+
     if (interactive()) {
       message(msg, "\nWould you like to install it?")
       if (utils::menu(c("Yes", "No")) == 1) {
@@ -300,7 +299,7 @@ check_suggests <- function(pkg) {
       }
     } else {
       stop(msg, call. = FALSE)
-    } 
+    }
   }
 
-}
+}