Pointwise, an integer-valued nonnegative random variable has the representation
when , exactly the terms equal one. Applying the Tonelli theorem, or the monotone convergence theorem to the finite sums of indicator random variables, gives the tail-sum formula for expectation
Both sides may be infinite; no integrability assumption is necessary.
Write and . Since is a stopping time, . The Tonelli theorem, conditional expectation, and (c)'s tail-sum formula for expectation yield
Thus is an integrable random variable. Since , telescoping gives and . The dominated convergence theorem gives , so (b) gives uniform integrability of the stopped martingale.
The optional stopping theorem at the bounded stopping time gives . Passing to the limit using the convergence in L1 proved in (b),
One can also pass directly by the dominated convergence theorem, since .
If is future time to dementia from age 50, its survival function is
The tail-sum formula for expectation gives the expected future time alive without dementia:
With administrative censoring at , one patient is observed to experience with probability
so
The observed time is , whose mean follows from the tail-sum formula for expectation:
Hence
Write for the partial sum. Fix an integer . The tail-sum formula for expectation, applied to the nonnegative random variable , gives
because . The events are independent, so the second Borel--Cantelli lemma shows that infinitely often with probability one. Taking the countable intersection over yields
almost surely.
Now , and the triangle inequality gives
If the limit superior of were finite, the right-hand side would have finite limit superior, contradicting the preceding conclusion. Therefore
almost surely.