Expected values for Perfect Information. Website for information is as follows: e_of_perfect_informationhttp://en.wikipedia.org/wiki/Expected_valu.

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Presentation transcript:

Expected values for Perfect Information

Website for information is as follows: e_of_perfect_informationhttp://en.wikipedia.org/wiki/Expected_valu e_of_perfect_information We will now use our classroom example to compute based on the above note next.

Formulae EVPI = A – B A = expected value with perfect information B = expected value without perfect information

example Consider our lecture example:

Calculation of A value A = the best of each outcome x their prob. The best of outcomes: Best outcome = 100,000 30,000 A = 0.6 x 100, x 30,000 = 72,000

Calculation of B value B = we select the max value of each given below Outcome of each event The max value for all computed value = 44, (50000) (30,000) = 42, (100, (40,000) = 44, (30,000) + 0.4(10,000) = 20,000

EVPI EVPI = A – B = 72,000 – 44,000 = 28,000

More examples! You can refer to the website provided for more example. We show these steps next:

0.5 for increase0.3 for equal20% decrease Option 11, Option Option 3500 EVPI = A – B A = expected value with perfect information B = expected value without perfect information For A: The optimal values for each value are: 0.5 for increase0.3 for equal20% decrease Option 11, Option Option 3500 Max value : 1, Thus A = 0.5 x 1, x x 500 = 1030 Consider:

For B: we compute the expected values for each column first, and then select the max as below: 0.5 for increase0.3 for equal20% decreaseMax value Option 11, x1, x x(- 800) = 680 Option x x x(-200) = 590 Option x x x500 = 500 Thus B = max of all max value of above = 680 EVPI = A – B = 1030 – 680 = 350

These steps also applied and worked for all examples shown in the tut as well. Good luck!