Uniform Accuracy of the Maximum Likelihood Estimates for Probabilistic Models of Biological Sequences

Svetlana Ekisheva and Mark Borodovsky ()
Additional contact information
Svetlana Ekisheva: Syktyvkar State University
Mark Borodovsky: Georgia Institute of Technology

Methodology and Computing in Applied Probability, 2011, vol. 13, issue 1, 105-120

Abstract: Abstract Probabilistic models for biological sequences (DNA and proteins) have many useful applications in bioinformatics. Normally, the values of parameters of these models have to be estimated from empirical data. However, even for the most common estimates, the maximum likelihood (ML) estimates, properties have not been completely explored. Here we assess the uniform accuracy of the ML estimates for models of several types: the independence model, the Markov chain and the hidden Markov model (HMM). Particularly, we derive rates of decay of the maximum estimation error by employing the measure concentration as well as the Gaussian approximation, and compare these rates.

Keywords: Maximum likelihood estimate; Asymptotic properties of estimates; Hidden Markov model; Concentration of measure; 62M05; 60J10; 62F10; 11L07 (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11009-009-9125-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:metcap:v:13:y:2011:i:1:d:10.1007_s11009-009-9125-7

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009

DOI: 10.1007/s11009-009-9125-7

Access Statistics for this article

Methodology and Computing in Applied Probability is currently edited by Joseph Glaz

More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().