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|parameters= — parameters of the distribution family (such as μ and σ 2 for the normal distribution). |support= — the support of the distribution, which may depend on the parameters. Specify this as <math>x \in some set</math> for continuous distributions, and as <math>k \in some set</math> for discrete distributions.
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Estimation of distribution algorithm. For each iteration i, a random draw is performed for a population P in a distribution PDu. The distribution parameters PDe are then estimated using the selected points PS. The illustrated example optimizes a continuous objective function f(X) with a unique optimum O.
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So if you are age 78 and you have an IRA balance of $100,000, your RMD for the year would be $4,545.45 (which is calculated by dividing your balance by distribution period years in the table above).
|parameters= — parameters of the distribution family (such as μ and σ 2 for the normal distribution). |support= — the support of the distribution, which may depend on the parameters. Specify this as <math>x \in some set</math> for continuous distributions, and as <math>k \in some set</math> for discrete distributions.
For example, a triangular distribution might be used, depending on the application. In three-point estimation, three figures are produced initially for every distribution that is required, based on prior experience or best-guesses: a = the best-case estimate; m = the most likely estimate; b = the worst-case estimate