Decision analysis with the decisionSupport package
Decision-makers often wish to have a quantitative basis for their decisions. However, there is often no ‘hard data’ for many important variables, which can paralyze decision-making processes or lead decision-makers to conclude that large research efforts are needed before a decision can be made. That is, many variables decision makers must consider cannot be precisely quantified, at least not without unreasonable effort. The major objective of (prescriptive) decision analysis is to support decision-making processes faced with this problem (Luedeling and Shepherd, 2016). Decision analysis can make forecasts of decision outcomes without precise numbers, as long as probability distributions describing the possible values for all variables can be estimated.