Let xi represent samples from a Truncated Exponential distribution between 0 and 1, with rate parameter λ.
What is the PDF of ˜x?
The solution is going to be an n-part piecewise pdf on (0,1). Given that the OP has noted he is interested in large n, expressing the exact pdf of the sample mean is likely to get messy. For large n (as given), one should obtain an excellent neat simple approximation via the Central Limit Theorem.
Let X∼TruncatedExponential(λ) (truncated above at 1), with pdf:
f(x)=λe−λx1−e−λ for 0<x<1
Then if the random variables X1,X2,... are iid, by the Central Limit Theorem:
All done. The following diagram compares:
- the EXACT distribution of the sample mean (blue curve) with
- the asymptotic Normal distribution (dashed red curve)
when the sample size is just n=6:
Even with this tiny sample size, the simple Normal approximation already performs well in the λ=1 case (LHS diagram). If λ becomes larger, the distribution becomes more peaked and shifts to the left, and larger sample sizes will be needed ... but will still perform extremely well for large n.
For comparison, the exact pdf when n=6 is:
Derivation of Exact PDF
To illustrate the calculation of the exact pdf, consider first two independent Truncated Exponential variables, say X and Y which will have joint pdf f(x,y):
Then, the cdf of S=X+Y, i.e. P(X+Y<s) is:
where I am using the
Prob function from the mathStatica package for Mathematica to automate the calculation.
The pdf of S=X+Yis just the derivative of the cdf wrt s:
Here is a plot of the exact pdf just derived in the n=2 case (here for the sample sum) when λ=1:
One can derive the exact pdf of the sample sum (or sample mean) for larger n in this same manner ... though for large n, the Central Limit Theorem will rapidly become your friend.