Statistics
Specialize
Specialize parameters
Calling Sequence
Parameters
Description
Examples
References
Specialize(X, eqns)
X
-
algebraic; random variable or distribution
eqns
list of equations, or a single equation, giving values for symbolic parameters in X
The Specialize function takes a random variable or distribution data structure that contains symbolic parameters, and performs a substitution to specialize the given random variable or distribution.
with⁡Statistics:
Create a random variable which is normally distributed with mean a and standard deviation b.
X≔RandomVariable⁡Normal⁡a,b
X≔_R
Mean⁡X,StandardDeviation⁡X
a,b
By setting a to 0, we obtain a random variable that is normally distributed with mean 0 and standard deviation b.
X1≔Specialize⁡X,a=0
X1≔_R0
Mean⁡X1,StandardDeviation⁡X1
0,b
Alternatively, we can set it so that mean and standard deviation are different functions of a single parameter c.
X2≔Specialize⁡X,a=c,b=c2
X2≔_R1
Mean⁡X2,StandardDeviation⁡X2
c,c2
Specialize also accepts algebraic expressions involving random variables.
Y≔X+b⁢X2
Y≔_R1⁢b+_R
Mean⁡Y,StandardDeviation⁡Y
b⁢c+a,b2⁢c4+b2
Y1≔Specialize⁡Y,b=a
Y1≔_R1⁢a+_R2
Mean⁡Y1,StandardDeviation⁡Y1
a⁢c+a,a2⁢c4+a2
If a parameter evaluates to a constant, then Maple will complain if that constant does not satisfy the requirements for the parameter. For example, the standard deviation cannot be negative.
Specialize⁡X,b=−1
Error, (in Statistics:-Specialize) invalid parameters obtained when substituting [b = -1]
Stuart, Alan, and Ord, Keith. Kendall's Advanced Theory of Statistics. 6th ed. London: Edward Arnold, 1998. Vol. 1: Distribution Theory.
See Also
Statistics[Distribution]
Statistics[MaximumLikelihoodEstimate]
Statistics[RandomVariable]
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