The sample keyword accumulates values across iterations of a
montecarlo block.
Examples
montecarlo 1000 with
x = random.uniform(-1, 1)
y = random.uniform(-1, 1)
inCircle = x^2 + y^2 < 1
sample approxPi = avg(if inCircle then 4 else 0)
show scalar "Pi approximation" with approxPi
This outputs the following scalar:
Pi approximation
3.224
montecarlo 1000 with
x = if random.binomial(0.2) then 0 else random.poisson(5)
sample r = ranvar(x)
show summary "Zero-inflated ranvar" with
mean(r) as "Mean"
dispersion(r) as "Disp"
This outputs the following summary:
Mean
Disp
4.116
1.895175
table T = extend.range(5)
montecarlo 1000 with
T.K = random.poisson(T.N)
sample T.ApproxMean = avg(T.K)
show table "Poisson means" with
T.N
T.ApproxMean
This outputs the following table:
N
ApproxMean
1
0.986
2
1.974
3
3.053
4
3.976
5
5.106
Remarks
At the moment, avg() and ranvar() are the only accumulators supported by
sample.