Package 'decision'

Title: Statistical Decision Analysis
Description: Contains a function called dmur() which accepts four parameters like possible values, probabilities of the values, selling cost and preparation cost. The dmur() function generates various numeric decision parameters like MEMV (Maximum (optimum) expected monitory value), best choice, EPPI (Expected profit with perfect information), EVPI (Expected value of the perfect information), EOL (Expected opportunity loss), which facilitate effective decision-making.
Authors: Partha Sarathi Bishnu <[email protected]>
Maintainer: Partha Sarathi Bishnu <[email protected]>
License: GPL (>= 2)
Version: 0.1.0
Built: 2024-11-08 06:22:54 UTC
Source: CRAN

Help Index


Statistical Decision Analysis: with the help of this package we construct the payoff table and the opportunity loss table and calculate various statistical parameters like EMVs, MEMV, EPPI, EVPI, EOL which help in taking effective decisions.

Description

Statistical Decision Analysis: with the help of this package we construct the payoff table and the opportunity loss table and calculate various statistical parameters like EMVs, MEMV, EPPI, EVPI, EOL which help in taking effective decisions.

Usage

dmur(dAmount, prob, sPrice, pPrice)

Arguments

dAmount

A data vector to store values

prob

A data vector to store the probabilities

sPrice

A numeric value to store selling price

pPrice

A numeric value to store preparation/ purchase price

Value

MEMV, bestValue, EPPI, EVPI, EOL

References

1. Khalili, k., Damghani, M. T., Taghavifard, R., Tavakkoli M., (2009) Decision making under uncertain and risky situations, Enterprise risk management symposium monograph society of Actuaries- Schaumburg, Illinois, vol. 15.

2. Marakas, G. M. (2006) Decision support system- In the 21st century, 2nd edition, Pearson education, New Delhi.

3. Turban, E., Aronson, J. E. and Liang, T.P. (2006) Decision support system and intelligent systems, Pearson education, New Delhi.

Examples

dmur(c(50, 100, 150, 200), c(0.2,0.4,0.3,0.1), 20, 10)