Purpose
It is used for setting discretized distribution of sprand.
Synopsis
spsetdist(rn: sprand, val: array() of real, prob: array() of real)
spsetdist(rns: set of sprand, val: array() of real, prob: array() of real)
Arguments
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rn
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independet stochastic random element
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rns
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jointly independet stochastic random elements
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val
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discrete values rn(s) may assume
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prob
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probabilities with which rn(s) assumes discrete values
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Example
Ex 1: Following code shows how to set an sprand's independent distribution
declarations
val,prob:array(1..3) of real
end-declarations
val:=[10,20,30];prob:=[0.2,0.5,0.3]
spsetdist(rn,val,prob)
Ex 2: Following code shows how to set joint distribution of set of sprands
! {return('Stock'),return('Bond'),return('Cash')}= [1.20, 1.08, 1.02] w.p 0.3
! = [0.90, 1.03, 1.00] w.p 0.7
declarations
Asset={'Stock','Bond','Cash'}
return: array(Asset) of sprand
rns: set of sprand
val:array(Asset,1..2) of real
prob:array(1..2) of real
end-declarations
rns:=union(i in Asset) {return(i)}; ! {return('Stock'),return('Bond'),return('Cash')}
val:=[1.20, 0.90, ! Stock
1.08, 1.03, ! Bond
1.02, 1.00]; ! Cash
prob:=[0.3, ! up branch
0.7]; ! down branch
spsetdist(rns,val,prob)
Further information
1. If rn belongs to first stage then by default it is equal to 0. Its value may however be changed by setting its ditribution
corresponding to a discrete value with probability 1.0.
2. If some sprands are jointly distributed then thier discetized distributions can be passed using the overloaded procedures.
3. Tree can be generated by calling spgenexh().
Related topics
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