Difference between revisions of "Mid"
(→Mid(x)) |
m (Typo, Uniform(1,1) should be Uniform(-1,1)) |
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Line 15: | Line 15: | ||
== Examples == | == Examples == | ||
− | Suppose <code>x := Uniform(1, 1)^2</code> | + | Suppose <code>x := Uniform(-1, 1)^2</code> |
:<code>Mid(x) → 0</code> | :<code>Mid(x) → 0</code> | ||
:<code>Median(x) → 0.25</code> | :<code>Median(x) → 0.25</code> |
Latest revision as of 18:08, 18 July 2017
Mid(x)
Evaluates «x» in Mid-Mode, i.e. deterministically.
Whenever an expression or subexpression is evaluated, it is evaluated either in Mid-mode or Sample-mode, in which sample-mode carries through information about uncertainty whereas mid-mode does not. The article on Evaluation Modes explains this in detail. Mid(x) forces the evaluation of «x» to occur in Mid-mode even when the current evaluation mode is sample-mode.
The Sample function does the opposite -- forcing «x» to be evaluated in sample mode.
Distribution functions return their median value in Mid-mode, or a Monte Carlo when evaluated in Sample-mode.
Mid is also used as an meta-expression in a MultiTable to show the computed value of «x».
Examples
Suppose x := Uniform(-1, 1)^2
Mid(x) → 0
Median(x) → 0.25
Mean(x) → 0.3333
When Mid is evaluated, the median value of Uniform(-1, 1)
is used, which is 0 and is then squared to get the mid-value of x
. As seen, this is not equivalent to the median of x
when uncertainty is properly accounted for.
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