Error exponents for composite hypothesis testing of Markov forest distributions
The problem of composite binary hypothesis testing of Markov forest (or tree) distributions is considered. The worst-case type-II error exponent is derived under the Neyman-Pearson formulation. Under simple null hypothesis, the error exponent is derived in closed-form and is characterized in terms o...
Main Authors: | , , |
---|---|
Other Authors: | |
Format: | Article |
Language: | en_US |
Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2012
|
Online Access: | http://hdl.handle.net/1721.1/73578 https://orcid.org/0000-0003-0149-5888 |