Estimating the Gumbel scale parameter for local alignment of random sequences by importance sampling with stopping times
DOI10.1214/08-AOS663zbMath1369.62255arXiv0909.0645OpenAlexW1974834242WikidataQ33530636 ScholiaQ33530636MaRDI QIDQ1043762
Sergey Sheetlin, Yonil Park, John L. Spouge
Publication date: 9 December 2009
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/0909.0645
importance samplingstopping timeMarkov renewal processMarkov additive processgapped sequence alignmentGumbel scale parameter estimation
Applications of statistics to biology and medical sciences; meta analysis (62P10) Markov processes: estimation; hidden Markov models (62M05) Inference from stochastic processes (62M99)
Uses Software
Cites Work
- Unnamed Item
- Non-negative matrices and Markov chains. 2nd ed
- Probability approximations via the Poisson clumping heuristic
- Some biological sequence metrics
- A phase transition for the score in matching random sequences allowing deletions
- Upper bounds and importance sampling of \(p\)-values of DNA and protein sequence alignments
- Sequence comparison significance and Poisson approximation
- Moderate deviations for Markov chains with atom.
- Approximate \(p\)-values for local sequence alignments.
- Limit distribution of maximal non-aligned two-sequence segmental score
- A limit theorem for matching random sequences allowing deletions
- A CONVEXITY PROPERTY OF POSITIVE MATRICES
- Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes.
- Rapid and accurate estimates of statistical significance for sequence data base searches.
- Accelerated convergence and robust asymptotic regression of the Gumbel scale parameter for gapped sequence alignment
- Path reversal, islands, and the gapped alignment of random sequences
- Applied Probability and Queues
- Robust Estimation of a Location Parameter
- Monte Carlo strategies in scientific computing
This page was built for publication: Estimating the Gumbel scale parameter for local alignment of random sequences by importance sampling with stopping times