Solution

ID: past-exam-of-the-mathematics-course-of-the-university-of-cambridge/2021/iii/paper-210/1/solution

A centered random variable is sub-Gaussian with parameter when
For , the Chernoff bound gives
Minimizing at yields . Applying the same argument to proves the left-tail bound.
The moment-generating-function inequality and its version at imply
Comparing the second-order terms as gives . Since ,
A centered is Sub-Gamma random variable in the right tail with variance factor and scale factor when
The corresponding Bernstein's inequality is
A standard squared-sub-Gaussian lemma, obtained by integrating the sub-Gaussian tail or expanding exponential moments, states that
Scaling a sub-Gamma variable by multiplies its variance factor by and its scale by ; independent sums add variance factors and take the largest scale. Decompose
Their sum is therefore sub-Gamma on the right with variance factor
and scale factor
Apply Bernstein to the sum at threshold to obtain

New to topics? Read the docs here!