Zobrazeno 1 - 10
of 12
pro vyhledávání: '"William G. Hanley"'
Publikováno v:
Geophysical Journal International. 177:193-204
SUMMARY We add probabilistic phase labels to the multiple-event joint probability function of Myers et al. that formerly included event locations, traveltime corrections and arrival-time measurement precision. Prior information on any of the multiple
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::632bce83ca5a9b3a5ccc0a1be3496f14
https://doi.org/10.1111/j.1365-246x.2008.04070.x
https://doi.org/10.1111/j.1365-246x.2008.04070.x
Autor:
Kathleen M. Dyer, Philip J. Vogt, Roger D. Aines, Gardar Johannesson, Gwen A. Loosmore, Rich D. Belles, Fotini Katopodes Chow, Shawn Larsen, Julie K. Lundquist, John J. Nitao, Luca Delle Monache, Branko Kosovic, William G. Hanley, Gayle A. Sugiyama
Publikováno v:
Journal of Applied Meteorology and Climatology. 47:2600-2613
A methodology combining Bayesian inference with Markov chain Monte Carlo (MCMC) sampling is applied to a real accidental radioactive release that occurred on a continental scale at the end of May 1998 near Algeciras, Spain. The source parameters (i.e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::06767da29d878bad23cd4dacb123f405
https://doi.org/10.1175/2008jamc1766.1
https://doi.org/10.1175/2008jamc1766.1
Publikováno v:
Computational Statistics. 20:177-196
The Gibbs sampler, being a popular routine amongst Markov chain Monte Carlo sampling methodologies, has revolutionized the application of Monte Carlo methods in statistical computing practice. The performance of the Gibbs sampler relies heavily on th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be0da8b0cc3d236f3071aa5337e10a6a
https://doi.org/10.1007/bf02736129
https://doi.org/10.1007/bf02736129
Publikováno v:
Computational Statistics & Data Analysis. 48:363-389
Markov chain Monte Carlo (MCMC) routines have revolutionized the application of Monte Carlo methods in statistical application and statistical computing methodology. The Hastings sampler, encompassing both the Gibbs and Metropolis samplers as special
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::91711130d909e6b84f00a9867efcd502
https://doi.org/10.1016/j.csda.2004.02.002
https://doi.org/10.1016/j.csda.2004.02.002
Publikováno v:
KDD
The generalization error, or probability of misclassification, of ensemble classifiers has been shown to be bounded above by a function of the mean correlation between the constituent (i.e., base) classifiers and their average strength. This bound su
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d8244fa1a418bb8407e4793287acf891
https://doi.org/10.1145/1835804.1835911
https://doi.org/10.1145/1835804.1835911
Publikováno v:
Annals of Information Systems ISBN: 9781441912794
Classification technologies have become increasingly vital to information analysis systems that rely upon collected data to make predictions or informed decisions. Many approaches have been developed, but one of the most successful in recent times is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6f84b8a79226b54b9e860cb2c8a006f8
https://doi.org/10.1007/978-1-4419-1280-0_6
https://doi.org/10.1007/978-1-4419-1280-0_6
Publikováno v:
CIDM
This paper presents the Cost-Sensitive Random Subspace Support Vector Classifier (CS-RS-SVC), a new learning algorithm that combines random subspace sampling and bagging with Cost-Sensitive Support Vector Classifiers to more effectively address detec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::65ab5470d9e51ebc82c293cfab7f28bd
https://doi.org/10.1109/cidm.2009.4938622
https://doi.org/10.1109/cidm.2009.4938622
Autor:
B Chen, G Clark, M Mugge, D Knapp, Milovan Krnjajic, John J. Nitao, William G. Hanley, L Hiller, T Hickling
In this project, the basic problem is to automatically separate test samples into one of two categories: clean or corrupt. This type of classification problem is known as a two-class classification problem or detection problem. In what follows, we re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba8b0561eb3bb6416a338c178220f3b4
https://doi.org/10.2172/922310
https://doi.org/10.2172/922310
Autor:
Shawn Larsen, Julie K. Lundquist, Arthur A. Mirin, Kathleen M. Dyer, William G. Hanley, Gardar Johannesson, Gwendolen A. Loosmore, Branko Kosovic
Publikováno v:
2006 IEEE Nonlinear Statistical Signal Processing Workshop.
The release of hazardous materials into the atmosphere can have a tremendous impact on dense populations. We propose an atmospheric event reconstruction framework that couples observed data and predictive computer-intensive dispersion models via Baye
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a28f4734db88349d4b58ba44da86dd5c
https://doi.org/10.1109/nsspw.2006.4378840
https://doi.org/10.1109/nsspw.2006.4378840
Autor:
William G. Hanley, Ronald E. Glaser, T L Hickling, Roger D. Aines, John J. Nitao, S Sengupta, Abelardo Ramirez, William Daily, Kathleen M. Dyer
Publikováno v:
Journal of Geophysical Research: Solid Earth. 110
[1] We describe a stochastic inversion method for mapping subsurface regions where the electrical resistivity is changing. The technique combines prior information, electrical resistance data, and forward models to produce subsurface resistivity mode
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f530d90e50998fbd3377a810bc070922
https://doi.org/10.1029/2004jb003449
https://doi.org/10.1029/2004jb003449