Notes on the sum and maximum of independent exponentially distributed random variables with different scale parameters
arXiv:1307.3945
Abstract
We consider the distribution of the sum and the maximum of a collection of independent exponentially distributed random variables. The focus is laid on the explicit form of the density functions (pdf) of non-i.i.d. sequences. Those are recovered in a simple and direct way based on conditioning. A connection between the pdf and a representation of the convolution characteristic function as a linear combination of the single characteristic functions is drawn. It is demonstrated how the results on the pdf of order statistics and the convolution merge.
Cited by in corpus (5)
- How Reliable and Capable is Multi-Connectivity?
- Performance Analysis of Joint Active User Detection and Channel Estimation for Massive Connectivity
- Maximum Likelihood Time Synchronization for Zero-padded OFDM
- Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification
- Variance of finite difference methods for reaction networks with non-Lipschitz rate functions