Removed save_kmeans

Merge branch 'master' into CRAN Conflicts: DESCRIPTION README.md build/build_mac_win.sh build/remove_screenshots.R inst/base/tools/app/about.md
vnijs · Mar 24, 2015 · f396a1e · f396a1e
2 parents ec0291b + 3d62ebc
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: radiant
 Title: Business Analytics using R and Shiny
-Version: 0.1.75
-Date: 2015-3-17
+Version: 0.1.83
+Date: 2015-3-24
 Authors@R: person("Vincent", "Nijs", , "radiant@rady.ucsd.edu", c("aut", "cre"))
 Description:
  A platform-independent browser-based interface for business analytics in R, based on the Shiny package.
@@ -31,7 +31,7 @@ Suggests:
  rmarkdown (>= 0.4.2),
  ggvis (>= 0.4),
  testthat (>= 0.9.1)
-URL: https://github.com/mostly-harmless/radiant, http://mostly-harmless.github.io/radiant/
-BugReports: https://github.com/mostly-harmless/radiant/issues
+URL: https://github.com/vnijs/radiant, http://vnijs.github.io/radiant/
+BugReports: https://github.com/vnijs/radiant/issues
 License: AGPL-3 | file LICENSE
 LazyData: true
diff --git a/NAMESPACE b/NAMESPACE
@@ -13,6 +13,7 @@ S3method(plot,kmeans_clus)
 S3method(plot,mds)
 S3method(plot,pmap)
 S3method(plot,pre_factor)
+S3method(plot,reg_predict)
 S3method(plot,regression)
 S3method(plot,single_mean)
 S3method(plot,single_prop)
@@ -62,7 +63,6 @@ export(sample_size)
 export(sampling)
 export(save_factors)
 export(save_glm_resid)
-export(save_kmeans)
 export(save_membership)
 export(save_reg_resid)
 export(set_class)

diff --git a/R/compare_means.R b/R/compare_means.R
@@ -1,6 +1,6 @@
 #' Compare means for two or more variables
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/compare_means.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/compare_means.html} for an example in Radiant
 #'
 #' @param dataset Dataset name (string). This can be a dataframe in the global environment or an element in an r_data list from Radiant
 #' @param cm_var1 A numeric variable or factor selected for comparison
@@ -80,7 +80,7 @@ compare_means <- function(dataset, cm_var1, cm_var2,
 
 #' Summary method for the compare_means function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/compare_means.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/compare_means.html} for an example in Radiant
 #'
 #' @param object Return value from \code{\link{compare_means}}
 #' @param ... further arguments passed to or from other methods
@@ -133,7 +133,7 @@ summary.compare_means <- function(object, ...) {
 
 #' Plot method for the compare_means function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/compare_means.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/compare_means.html} for an example in Radiant
 #'
 #' @param x Return value from \code{\link{compare_means}}
 #' @param cm_plots One or more plots ("bar", "box", or "density")

diff --git a/R/compare_props.R b/R/compare_props.R
@@ -1,6 +1,6 @@
 #' Compare proportions across groups
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/compare_props.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/compare_props.html} for an example in Radiant
 #'
 #' @param dataset Dataset name (string). This can be a dataframe in the global environment or an element in an r_data list from Radiant
 #' @param cp_var1 A grouping variable to split the data for comparisons
@@ -93,7 +93,7 @@ compare_props <- function(dataset, cp_var1, cp_var2,
 
 #' Summary method for the compare_props function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/compare_props.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/compare_props.html} for an example in Radiant
 #'
 #' @param object Return value from \code{\link{compare_props}}
 #' @param ... further arguments passed to or from other methods
@@ -144,7 +144,7 @@ summary.compare_props <- function(object, ...) {
 
 #' Plot method for the compare_props function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/compare_props.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/compare_props.html} for an example in Radiant
 #'
 #' @param x Return value from \code{\link{compare_props}}
 #' @param cp_plots One or more plots of proportions or counts ("props" or "counts")

diff --git a/R/conjoint.R b/R/conjoint.R
@@ -1,6 +1,6 @@
 #' Conjoint analysis
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/marketing/conjoint.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/marketing/conjoint.html} for an example in Radiant
 #'
 #' @param dataset Dataset name (string). This can be a dataframe in the global environment or an element in an r_data list from Radiant
 #' @param ca_dep_var The dependent variable (e.g., profile ratings)
@@ -44,7 +44,7 @@ conjoint <- function(dataset, ca_dep_var, ca_indep_var,
 
 #' Summary method for the conjoint function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/marketing/conjoint.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/marketing/conjoint.html} for an example in Radiant
 #'
 #' @param object Return value from \code{\link{conjoint}}
 #' @param ca_vif Shows multicollinearity diagnostics.
@@ -104,7 +104,7 @@ summary.conjoint <- function(object,
 
 #' Plot method for the conjoint function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/marketing/conjoint.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/marketing/conjoint.html} for an example in Radiant
 #'
 #' @param x Return value from \code{\link{conjoint}}
 #' @param ca_plots Show either the part-worth ("pw") or importance-weights ("iw") plot
@@ -164,7 +164,7 @@ plot.conjoint <- function(x,
 
 #' Function to calculate the PW and IW table for conjoint
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/marketing/conjoint.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/marketing/conjoint.html} for an example in Radiant
 #'
 #' @param model Tidied model results (broom) output from \code{\link{conjoint}} passed on by summary.conjoint
 #' @param dat Conjoint data

diff --git a/R/conjoint_profiles.R b/R/conjoint_profiles.R
@@ -1,6 +1,6 @@
 #' Create fractional factorial design for conjoint analysis
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/marketing/conjoint_profiles.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/marketing/conjoint_profiles.html} for an example in Radiant
 #'
 #' @param dataset Dataset name (string). This can be a dataframe in the global environment or an element in an r_data list from Radiant
 #'
@@ -47,7 +47,7 @@ conjoint_profiles <- function(dataset) {
 
 #' Summary method for the conjoint_profiles function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/marketing/conjoint_profiles.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/marketing/conjoint_profiles.html} for an example in Radiant
 #'
 #' @param object Return value from \code{\link{conjoint_profiles}}
 #' @param ... further arguments passed to or from other methods.
@@ -81,7 +81,7 @@ summary.conjoint_profiles <- function(object, ...) {
 
 #' Function to generate a fractional factorial design
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/marketing/conjoint_profiles.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/marketing/conjoint_profiles.html} for an example in Radiant
 #'
 #' @param attr Attributes used to generate profiles
 #' @param trial Number of trials that have already been run

diff --git a/R/correlation.R b/R/correlation.R
@@ -1,6 +1,6 @@
 #' Calculate correlations for two or more variables
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/correlation.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/correlation.html} for an example in Radiant
 #'
 #' @param dataset Dataset name (string). This can be a dataframe in the global environment or an element in an r_data list from Radiant
 #' @param cor_var Variables to include in the analysis
@@ -34,7 +34,7 @@ correlation <- function(dataset, cor_var,
 
 #' Summary method for the correlation function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/correlation.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/correlation.html} for an example in Radiant
 #'
 #' @param object Return value from \code{\link{correlation}}
 #' @param cor_cutoff Show only corrlations larger than the cutoff in absolute value. Default is a cutoff of 0
@@ -81,7 +81,7 @@ summary.correlation <- function(object,
 
 #' Plot method for the correlation function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/correlation.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/correlation.html} for an example in Radiant
 #'
 #' @param x Return value from \code{\link{correlation}}
 #' @param ... further arguments passed to or from other methods.

diff --git a/R/cross_tabs.R b/R/cross_tabs.R
@@ -1,6 +1,6 @@
 #' Evaluate associations between categorical variables
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/cross_tabs.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/cross_tabs.html} for an example in Radiant
 #'
 #' @param dataset Dataset name (string). This can be a dataframe in the global environment or an element in an r_data list from Radiant
 #' @param ct_var1 A categorical variable
@@ -37,7 +37,7 @@ cross_tabs <- function(dataset, ct_var1, ct_var2,
 
 #' Summary method for the cross_tabs function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/cross_tabs.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/cross_tabs.html} for an example in Radiant
 
 #' @param object Return value from \code{\link{cross_tabs}}
 #' @param ct_check Show table(s) for variables ct_var1 and ct_var2. "observed" for the observed frequencies table, "expected" for the expected frequencies table (i.e., frequencies that would be expected if the null hypothesis holds), "chi_sq" for the contribution to the overall chi-squared statistic for each cell (i.e., (o - e)^2 / e), "dev_std" for the standardized differences between the observed and expected frequencies (i.e., (o - e) / sqrt(e)), and "dev_perc" for the percentage difference between the observed and expected frequencies (i.e., (o - e) / e)
@@ -129,7 +129,7 @@ summary.cross_tabs <- function(object,
 
 #' Plot method for the cross_tabs function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/cross_tabs.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/cross_tabs.html} for an example in Radiant
 #'
 #' @param x Return value from \code{\link{cross_tabs}}
 #' @param ct_check Show plots for variables ct_var1 and ct_var2. "observed" for the observed frequencies table, "expected" for the expected frequencies table (i.e., frequencies that would be expected if the null hypothesis holds), "chi_sq" for the contribution to the overall chi-squared statistic for each cell (i.e., (o - e)^2 / e), "dev_std" for the standardized differences between the observed and expected frequencies (i.e., (o - e) / sqrt(e)), and "dev_perc" for the percentage difference between the observed and expected frequencies (i.e., (o - e) / e)

diff --git a/R/full_factor.R b/R/full_factor.R
@@ -1,6 +1,6 @@
 #' Factor analysis (PCA)
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/marketing/full_factor.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/marketing/full_factor.html} for an example in Radiant
 #'
 #' @param dataset Dataset name (string). This can be a dataframe in the global environment or an element in an r_data list from Radiant
 #' @param ff_var Variables to include in the analysis
@@ -58,7 +58,7 @@ full_factor <- function(dataset, ff_var,
 
 #' Summary method for the full_factor function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/marketing/full_factor.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/marketing/full_factor.html} for an example in Radiant
 #'
 #' @param object Return value from \code{\link{full_factor}}
 #' @param ff_cutoff Show only loadings with (absolute) values above ff_cutoff (default = 0)
@@ -138,7 +138,7 @@ summary.full_factor <- function(object,
 
 #' Plot method for the full_factor function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/marketing/full_factor.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/marketing/full_factor.html} for an example in Radiant
 #'
 #' @param x Return value from \code{\link{full_factor}}
 #' @param ... further arguments passed to or from other methods
@@ -190,7 +190,7 @@ plot.full_factor <- function(x, ...) {
 
 #' Save factor scores to active dataset
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/marketing/full_factor.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/marketing/full_factor.html} for an example in Radiant
 #'
 #' @param object Return value from \code{\link{full_factor}}
 #'

diff --git a/R/glm_reg.R b/R/glm_reg.R
@@ -1,6 +1,6 @@
 #' Generalized linear models (GLM)
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/glm_reg.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/glm_reg.html} for an example in Radiant
 #'
 #' @param dataset Dataset name (string). This can be a dataframe in the global environment or an element in an r_data list from Radiant
 #' @param glm_dep_var The dependent variable in the logit (probit) model
@@ -80,7 +80,7 @@ glm_reg <- function(dataset, glm_dep_var, glm_indep_var,
 
 #' Summary method for the glm_reg function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/glm_reg.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/glm_reg.html} for an example in Radiant
 #'
 #' @param object Return value from \code{\link{glm_reg}}
 #' @param glm_sum_check Optional output or estimation parameters. "rsme" to show the root mean squared error. "sumsquares" to show the sum of squares table. "vif" to show multicollinearity diagnostics. "confint" to show coefficient confidence interval estimates.
@@ -230,7 +230,7 @@ summary.glm_reg <- function(object,
 
 #' Plot method for the glm_reg function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/glm_reg.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/glm_reg.html} for an example in Radiant
 #'
 #' @param x Return value from \code{\link{glm_reg}}
 #' @param glm_plots Plots to produce for the specified GLM model. Use "" to avoid showing any plots (default). "hist" shows histograms of all variables in the model. "scatter" shows scatter plots (or box plots for factors) for the dependent variable with each independent variable. "dashboard" is a series of four plots used to visually evaluate model. "coef" provides a coefficient plot
@@ -329,7 +329,7 @@ plot.glm_reg <- function(x,
 
 #' Predict method for the glm_reg function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/glm_reg} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/glm_reg.html} for an example in Radiant
 #'
 #' @param object Return value from \code{\link{glm_reg}}
 #' @param glm_predict_cmd Generate predictions using a command. For example, `pclass = levels(pclass)` would produce predictions for the different levels of factor `pclass`. To add another variable use a `,` (e.g., `pclass = levels(pclass), age = seq(0,100,20)`)
@@ -338,9 +338,7 @@ plot.glm_reg <- function(x,
 #'
 #' @examples
 #' result <- glm_reg("titanic", "survived", c("pclass","sex"), glm_levels = "Yes")
-#' pred <- predict(result, glm_predict_cmd = "pclass = levels(pclass)")
-#' str(pred)
-#' names(pred)
+#' predict(result, glm_predict_cmd = "pclass = levels(pclass)")
 #' predict(result, glm_predict_cmd = "sex = c('male','female')")
 #'
 #' @seealso \code{\link{glm_reg}} to generate the result
@@ -457,7 +455,7 @@ predict.glm_reg <- function(object,
 
 #' Plot method for the predict.glm_reg function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/glm_reg} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/glm_reg.html} for an example in Radiant
 #'
 #' @param x Return value from \code{\link{predict.glm_reg}}.
 #' @param glm_xvar Variable to display along the X-axis of the plot
@@ -527,7 +525,7 @@ plot.glm_predict <- function(x,
 
 #' Save residuals generated in the glm_reg function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/quant/glm_reg.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/quant/glm_reg.html} for an example in Radiant
 #'
 #' @param object Return value from \code{\link{glm_reg}}
 #'

diff --git a/R/hier_clus.R b/R/hier_clus.R
@@ -1,6 +1,6 @@
 #' Hierarchical cluster analysis
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/marketing/hier_clus.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/marketing/hier_clus.html} for an example in Radiant
 #'
 #' @param dataset Dataset name (string). This can be a dataframe in the global environment or an element in an r_data list from Radiant
 #' @param hc_vars Vector of variables to include in the analysis
@@ -36,7 +36,7 @@ hier_clus <- function(dataset, hc_vars,
 
 #' Summary method for the hier_clus function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/marketing/hier_clus.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/marketing/hier_clus.html} for an example in Radiant
 #'
 #' @param object Return value from \code{\link{hier_clus}}
 #' @param ... further arguments passed to or from other methods
@@ -63,7 +63,7 @@ summary.hier_clus <- function(object, ...) {
 
 #' Plot method for the hier_clus function
 #'
-#' @details See \url{http://mostly-harmless.github.io/radiant/marketing/hier_clus.html} for an example in Radiant
+#' @details See \url{http://vnijs.github.io/radiant/marketing/hier_clus.html} for an example in Radiant
 #'
 #' @param x Return value from \code{\link{hier_clus}}
 #' @param hc_plots Plots to return. "diff" shows the percentage change in within-cluster heterogeneity as respondents are group into different number of clusters, "dendro" shows the dendrogram, "scree" shows a scree plot of within-cluster heterogeneity