report: Generates report about a conducted igate.
In igate: Guided Analytics for Testing Manufacturing Parameters

Description Usage Arguments Value Examples

Takes results from a previous igate and automatically generates a html report for it. Be aware that running this function will create an html document in your current working directory.

report(df, versus = 8, target, type = "continuous", test = "w",
  ssv = NULL, outlier_removal_target = TRUE,
  outlier_removal_ssv = TRUE, good_outcome = "low", results_path,
  validation = FALSE, validation_path = NULL,
  validation_counts = NULL, validation_summary = NULL,
  image_directory = tempdir(), output_name = NULL, output_directory)

`df`	The data frame that was analysed with `igate` or `categorical.igate`.
`versus`	What value of `versus` was used?
`target`	What `target` was used?
`type`	Was `igate` (use `type = "continuous"`) or `categorical.igate` (use `type = "categorical"`) conducted?
`test`	Which hypothesis test was used alongside the counting method?
`ssv`	Which `ssv` have been used in the analysis? If `NULL`, it will be assumed that `ssv = NULL` was passed to `igate` or `categorical.igate` and all numeric variables in `df` will be used.
`outlier_removal_target`	Was outlier removal conducted for `target`? If `type == "categorical"` this is set to `FALSE` automatically.
`outlier_removal_ssv`	Was outlier removal conducted for each `ssv`?
`good_outcome`	Are `"low"` or `"high"` values of `target` good? Or, in case of a categorical `target` the name of the best category as a string.
`results_path`	Name of R object (as string) containing the results of `igate` or `categorical.igate`.
`validation`	Logical. Has validation of the results been performed?
`validation_path`	Name R object (as string) containing the validated observations, i.e. first data frame returned by `validate`.
`validation_counts`	Name of R object (as string) containing the counts from validation, i.e. the second data frame returned by `validate`.
`validation_summary`	Name of R object (as string) containing the summary of `validation_path`, i.e. the third data frame returned by `validate`.
`image_directory`	Directory which contains the plots from `igate`, `igate.regressions` etc.
`output_name`	Desired name of the output file. File extension .html will be added automatically if not supplied. If `NULL` will be iGATE_Report.html.
`output_directory`	Directory into which the report should be saved. To save to the current working directory, use `output_directory = getwd()`.

An html file named "iGATE_Report.html" will be output to the current working directory, containing details about the conducted analysis. This includes a list of the analysed SSV, as well as tables with the results from igate/ categorical.igate and plots from igate.regressions/ categorical.freqplot.

## Example for categorical target variable
# If you want to conduct an igate analysis from scratch, running report
# is the last step and relies on executing the other functions in this package first.
# Run categorical.igate
df <- mtcars
df$cyl <- as.factor(df$cyl)
results <- categorical.igate(df, target = "cyl", best.cat = "8", worst.cat = "4")
# Produce density plots
# Suppose you only want to analyse further the first three identified ssv
results <- results[1:3,]
categorical.freqplot(mtcars, target = "cyl", ssv = results$Causes , savePlots = TRUE)

report(df = df, target = "cyl", type = "categorical", good_outcome = "8",
results_path = "results",
output_name = "testing_igate", output_directory = tempdir())