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Items: 1 to 20 of 116

1.

Bayesian selection of Markov models for symbol sequences: application to microsaccadic eye movements.

Bettenbühl M, Rusconi M, Engbert R, Holschneider M.

PLoS One. 2012;7(9):e43388. doi: 10.1371/journal.pone.0043388. Epub 2012 Sep 6.

2.

A Bayesian method for construction of Markov models to describe dynamics on various time-scales.

Rains EK, Andersen HC.

J Chem Phys. 2010 Oct 14;133(14):144113. doi: 10.1063/1.3496438.

PMID:
20949993
3.

Bayesian inference for stochastic kinetic models using a diffusion approximation.

Golightly A, Wilkinson DJ.

Biometrics. 2005 Sep;61(3):781-8.

PMID:
16135029
4.

Toward a model of microsaccade generation: the case of microsaccadic inhibition.

Rolfs M, Kliegl R, Engbert R.

J Vis. 2008 Aug 6;8(11):5.1-23. doi: 10.1167/8.11.5.

PMID:
18831599
5.

Data cloning: easy maximum likelihood estimation for complex ecological models using Bayesian Markov chain Monte Carlo methods.

Lele SR, Dennis B, Lutscher F.

Ecol Lett. 2007 Jul;10(7):551-63. Erratum in: Ecol Lett. 2007 Sep;10(9):866.

PMID:
17542934
6.

Bayesian clustering of DNA sequences using Markov chains and a stochastic partition model.

Jääskinen V, Parkkinen V, Cheng L, Corander J.

Stat Appl Genet Mol Biol. 2014 Feb;13(1):105-21. doi: 10.1515/sagmb-2013-0031.

PMID:
24246289
7.

Inferring Markov chains: Bayesian estimation, model comparison, entropy rate, and out-of-class modeling.

Strelioff CC, Crutchfield JP, Hübler AW.

Phys Rev E Stat Nonlin Soft Matter Phys. 2007 Jul;76(1 Pt 1):011106. Epub 2007 Jul 12. Erratum in: Phys Rev E Stat Nonlin Soft Matter Phys. 2007 Jul;76(2 Pt 2):019902.

PMID:
17677409
8.

Bayesian inference of phylogeny and its impact on evolutionary biology.

Huelsenbeck JP, Ronquist F, Nielsen R, Bollback JP.

Science. 2001 Dec 14;294(5550):2310-4.

PMID:
11743192
9.

Statistical inference for stochastic simulation models--theory and application.

Hartig F, Calabrese JM, Reineking B, Wiegand T, Huth A.

Ecol Lett. 2011 Aug;14(8):816-27. doi: 10.1111/j.1461-0248.2011.01640.x. Epub 2011 Jun 17. Review.

PMID:
21679289
10.

Optimal instruments and models for noisy chaos.

Strelioff CC, Crutchfield JP.

Chaos. 2007 Dec;17(4):043127. doi: 10.1063/1.2818152.

PMID:
18163791
11.

An inverse Yarbus process: predicting observers' task from eye movement patterns.

Haji-Abolhassani A, Clark JJ.

Vision Res. 2014 Oct;103:127-42. doi: 10.1016/j.visres.2014.08.014. Epub 2014 Aug 28.

13.

ToPS: a framework to manipulate probabilistic models of sequence data.

Kashiwabara AY, Bonadio I, Onuchic V, Amado F, Mathias R, Durham AM.

PLoS Comput Biol. 2013;9(10):e1003234. doi: 10.1371/journal.pcbi.1003234. Epub 2013 Oct 3.

14.

Bayesian mixture modeling using a hybrid sampler with application to protein subfamily identification.

Fong Y, Wakefield J, Rice K.

Biostatistics. 2010 Jan;11(1):18-33. doi: 10.1093/biostatistics/kxp033. Epub 2009 Aug 20.

15.

Bayesian internal dosimetry calculations using Markov Chain Monte Carlo.

Miller G, Martz HF, Little TT, Guilmette R.

Radiat Prot Dosimetry. 2002;98(2):191-8.

PMID:
11926369
16.

Bayesian Markov switching models for the early detection of influenza epidemics.

Martínez-Beneito MA, Conesa D, López-Quílez A, López-Maside A.

Stat Med. 2008 Sep 30;27(22):4455-68. doi: 10.1002/sim.3320.

PMID:
18618414
17.

Identification of transcription factor binding sites with variable-order Bayesian networks.

Ben-Gal I, Shani A, Gohr A, Grau J, Arviv S, Shmilovici A, Posch S, Grosse I.

Bioinformatics. 2005 Jun 1;21(11):2657-66. Epub 2005 Mar 29.

18.

Object and scene analysis by saccadic eye-movements: an investigation with higher-order statistics.

Krieger G, Rentschler I, Hauske G, Schill K, Zetzsche C.

Spat Vis. 2000;13(2-3):201-14.

PMID:
11198232
19.

Bayesian analysis of non-homogeneous Markov chains: application to mental health data.

Sung M, Soyer R, Nhan N.

Stat Med. 2007 Jul 10;26(15):3000-17.

PMID:
17173342
20.
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