Contains all data sets for Exam PA: Predictive Analytics at 
    <https://exampa.net/>.

Take the examples written in your documentation of functions
    and use them to create shells (skeletons which must be manually
    completed by the user) of test files to be tested with the 'testthat'
    package. Sort of like python 'doctests' for R.

Automatic generation of exams based on exercises in Markdown or LaTeX format,
	possibly including R code for dynamic generation of exercise elements.
	Exercise types include single-choice and multiple-choice questions, arithmetic problems,
	string questions, and combinations thereof (cloze). Output formats include standalone
	files (PDF, HTML, Docx, ODT, ...), Moodle XML, QTI 1.2, QTI 2.1, Blackboard, Canvas, OpenOlat, ILIAS, TestVision,
	Particify, ARSnova, Kahoot!, Grasple, and TCExam. In addition to fully customizable PDF exams, a standardized PDF format
	(NOPS) is provided that can be printed, scanned, and automatically evaluated.

Randomized multiple-select and single-select
  question generation for the 'MyLearn' teaching and learning
  platform. Question templates
  in the form of the R/exams package (see <http://www.r-exams.org/>)
  are transformed into XML format required by 'MyLearn'.

Automatic generation of quizzes or individual questions for 'learnr' tutorials based on 'R/exams' exercises.

Automatic Generation of Exams in R for 'Sakai'.
  Question templates in the form of the 'exams' package (see <http://www.r-exams.org/>)
  are transformed into XML format required by 'Sakai'.

Provides methods for constructing confidence or credible regions
    for exceedance sets and contour lines.

Computes confidence intervals for the exceedance probability of normally distributed estimators. Currently only supports general linear models. Please see Segal (2019) <arXiv:1803.03356> for more information.

Allows access to data in running instance of Microsoft Excel
    (e. g. 'xl[a1] = xl[b2]*3' and so on). Graphics can be transferred with
    'xl[a1] = current.graphics()'. Additionally there are function for reading/writing 
    'Excel' files - 'xl.read.file'/'xl.save.file'. They are not fast but able to read/write 
    '*.xlsb'-files and password-protected files. There is an Excel workbook with 
    examples of calling R from Excel in the 'doc' folder. It tries to keep things as
    simple as possible - there are no needs in any additional
    installations besides R, only 'VBA' code in the Excel workbook.
    Microsoft Excel is required for this package.