On Identifying a Massive Number of Distributions
classification
💻 cs.IT
math.IT
keywords
distributionsnumberobservedprobabilitysequencesasymptoticallyblocklengthbounds
read the original abstract
Finding the underlying probability distributions of a set of observed sequences under the constraint that each sequence is generated i.i.d by a distinct distribution is considered. The number of distributions, and hence the number of observed sequences, are let to grow with the observation blocklength $n$. Asymptotically matching upper and lower bounds on the probability of error are derived.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.