반응형 산업공학/Decision Science6 QALY (Quality - adjusted life year) QALY 에 대한 위키피디아의 정의는 아래와 같다. The quality-adjusted life year or quality-adjusted life-year (QALY) is a measure of disease burden, including both the quality and the quantity of life lived. It is used in assessing the value for money of a medical intervention. According to Pliskin et al., The QALY model requires utility independent, risk neutral, and constant proportional tradeoff behaviour. The Q.. 2024. 3. 5. Critical Path Analysis Critical Path Analysis ex) 1. ES (earliest start) - Earliest start time given predecessor activities 2. EF (earliest finish) - Earliest possible completion time 3. LS (latest start) - Latest start time as to not delay entire project 4. LF (latest finish) - Latest finish time as to not delay entire project 1) Forward Pass - Proceed through diagram from strat to finish 다이아그램의 시작부터 시간을 계산해 나감 - ES.. 2024. 3. 5. Bracket median method Bracket Median Method. Continuous distribution을 discrete approximation 하는 방법 2번째 (Tukey method에 이어) - The bracket median method of interval [a,b] is a value m* between a and b such that P(a 2024. 3. 5. EVPI (expected value of perfect information) Expected Value of Perfect Information. : quantity as the maximum amount that the investor should be willing to pay the clairvoyant for perfect information. (출처: Figure. Making hard decision chapter12 pg.440) 그림을 보면, 정보가 없는 decision node에서 나오는 EMV는 high risk 일때 580이다. Consult Clairvoyant, 즉, perfect information 이 제공되는 경우, investor의 행동을 보면 market이 up 일때는 high rist stock을, market이 flat일때는 savings a.. 2024. 3. 5. certainty equivalent certainty equivalent : 확실성등가란 위험있는 수익흐름에 대하여 그 위험을 부담하는 대신 보다 적은 수익이라도 확실하게 실현될 수 있다면 그와 맞바꿀 수 있는 최소한의 가격 (네이버 지식백과) : the amount of money that is equivalent in your mind to a given situation that involves uncertainty. (making hard decision 2nd edi) 예를 들어 이해해 보도록하자, win $2,000 with probability 0.50, lose $20 with probability 0.50 인 복권의 상황을 가정해보자. 만약 친구가 나 대신 위의 복권을 사려고 한다. 얼마에 저 기회를 양보하겠는가? $300.. 2024. 3. 5. Extended Pearson-Tukey The easiest way to use a continuous distribution in a decision tree or influence diagram is to approximate it with a discrete distribution. The basic idea is to find a few representative points in the distribution and then to assign those points specific probability value. A particularly simple approach, from Keefer and Bodily (1983), is called the extended Pearson-Turkey method. (Source: Making.. 2024. 3. 5. 이전 1 다음 반응형
