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| University of Cambridge > Department of Engineering > Signal Processing Group > Adam Johansen |
| [1] |
A. M. Johansen, P. Del Moral, and A. Doucet.
Sequential Monte Carlo samplers for rare events.
In Proceedings of the 6th International Workshop on Rare Event
Simulation, Bamberg, Germany, October 2006.
To appear. [ bib | .djvu | .ps | .pdf ] |
| [2] |
A. M. Johansen, S. S. Singh, A. Doucet, and B.-N. Vo.
Convergence of the SMC implementation of the PHD filter.
Methodology and Computing in Applied Probability,
8(2):265-291, June 2006. [ bib | http ] |
| [3] |
A. M. Johansen, A. Doucet, and M. Davy.
Maximum likelihood parmeter estimation for maximum likelihood models
using sequential Monte Carlo.
In Proceedings of ICASSP, volume III, pages 640-643. IEEE,
May 2006. [ bib | .djvu | .ps | .pdf ] |
| [4] |
A. M. Johansen, P. Del Moral, and A. Doucet.
Sequential Monte Carlo samplers for rare event estimation.
Technical Report CUED/F-INFENG/TR-543, University of Cambridge,
Department of Engineering, Cambridge University Engineering Department,
Trumpington Street, Cambridge, CB2 1PZ, 2006.
In preparation. [ bib ] |
| [5] |
P. Fearnhead.
Perfect simulation from non-neutral population genetic models:
Variable population size and population sub-division.
Genetics, 2006.
To appear. [ bib ] |
| [6] |
S. A. Astakhov, H. Stögbauer, A. Kraskov, and P. Grassberger.
Monte Carlo algorithm for least dependent non-negative mixture
decomposition.
ArXiv Mathematics e-prints, physics(0601161v1), January 2006. [ bib | http ] |
| [7] |
C. C. Holmes and L. Held.
Bayesian auxiliary variable models for binary and polychotomous
regression.
Bayesian Analysis, 2006.
To Appear. [ bib | .pdf ] |
| [8] |
I. Cowley and S. Thomas.
An unexpected artefact with low-contrast high-energy film.
Physics in Medicine and Biology, 51:N17-N21, January 2006. [ bib | http ] |
| [9] |
A. Lagnoux.
Rare event simulation.
Probability in the Engineering and Informational Sciences,
20(1):43-66, 2006. [ bib ] |
| [10] |
R. J. Allen, D. Frenkel, and P. R. ten Wolde.
Simulating rare events in equilibrium or non-equilibrium stochastic
systems.
Journal of Chemical Physics, 124(024102):1-16, 2006. [ bib ] |
| [11] |
P. Del Moral, A. Doucet, and A. Jasra.
Sequential Monte Carlo methods for Bayesian Computation.
In Bayesian Statistics 8. Oxford University Press, 2006.
To Appear. [ bib ] |
| [12] |
P. Del Moral, A. Doucet, and A. Jasra.
Sequential Monte Carlo samplers.
Journal of the Royal Statistical Society B, 63(3):411-436,
2006. [ bib ] |
| [13] |
A. Doucet, M. Briers, and S. Sénécal.
Efficient block sampling strategies for sequential Monte Carlo
methods.
Journal of Computational and Graphical Statistics, 2006.
To Appear. [ bib | .pdf ] |
| [14] |
A. Doucet, L. Montesano, and A. Jasra.
Optimal filtering for partially observed point processes using
trans-dimensional monte carlo.
In Proceedings of IEEE ICASSP, 2006.
To appear. [ bib ] |
| [15] |
A. Jasra and A. Doucet.
Stability of sequential Monte Carlo samplers via the
Foster-Lyapunov condition.
Submitted, 2006. [ bib ] |
| [16] |
J. Garnier and P. Del Moral.
Simulations of rare events in fibre optics by interacting particle
systems.
Elsevier Science, 2006.
Submitted. [ bib | www: ] |
| [17] |
A. Jasra, A. Doucet, D. A. Stephens, and C. C. Holmes.
Stratified sequential monte carlo samplers for trans-dimensional
simulation.
2006.
Submitted. [ bib ] |
| [18] |
A. Jasra, D. A. Stephens, and C. C. Holmes.
On population-based simulation for static inference.
2006.
Submitted. [ bib ] |
| [19] |
A. Jasra, D. A. Stephens, and C. C. Holmes.
Population-based reversible jump markov chain monte carlo.
2006.
In Preparation. [ bib ] |
| [20] |
Tomaz Podobnik and Tomi Zivko.
Towards reconciliation between bayesian and frequentist reasoning.
ArXiv Mathematics e-prints, math.ST(0510628v1), November
2005. [ bib ] |
| [21] |
P. Del Moral and J. Garnier.
Genealogical particle analysis of rare events.
Annals of Applied Probability, 15(4):2496-2534, November 2005. [ bib | http ] |
| [22] |
B. Vo, S.S. Singh, and A. Doucet.
Sequential Monte Carlo methods for multi-target filtering with
random finite sets.
IEEE Transactions on Aerospace and Electronic Systems,
41(4):1223-1245, October 2005. [ bib | .pdf ] |
| [23] |
F. Cérou and A. Guyader.
Adaptive multilevel splitting for rare event analysis.
Research Report 5710, INRIA, October 2005. [ bib ] |
| [24] |
L. M. Birch.
Computational Insights into Protein-Ligand Interactions.
Ph.D. thesis, University of Cambridge, Department of Chemistry,
Lensfield Road, Cambridge, UK, August 2005. [ bib ] |
| [25] |
Brenda Ng, Avi Pfeffer, and Richard Dearden.
Continuous time particle filtering.
In Proceedings of the 19th International Joint Conference on
Artificial Intelligence, August 2005. [ bib | .pdf ] |
| [26] |
Karthik Gopalratnam, Henry Kautz, and Daniel S. Weld.
Extending continuous time Bayesian networks.
In Proceedings of the twentieth AAAI national congress on
artificial intelligence. American Association for Artificial Intelligence,
July 2005. [ bib | .pdf ] |
| [27] |
G. L. Litvinov.
The Maslov dequantiszation, idempotent and tropical mathematics: A
brief introduction.
ArXiv Mathematics e-prints, GM(0507014v1), July 2005. [ bib | http ] |
| [28] |
J. Ching, J. L Beck, and S. K. Au.
Hybrid subset simulation method for reliability estimation of
dynamical systems subject to stochastic excitation.
Probabilistic Engineering Mechanics, 20(3):199-214, July 2005. [ bib ] |
| [29] |
Pavel Okunev and Charles R. Johnson.
Necessary and sufficient conditions for existence of the LU
factorization of an arbitrary matrix.
ArXiv Mathematics e-prints, NA(0506382), June 2005. [ bib | http ] |
| [30] |
Inder Jeet Taneja.
Relative divergence measures and information inequalities.
ArXiv Mathematics e-prints, PR(0505204v1):1-29, May 2005. [ bib | http ] |
| [31] |
S. Malefaki and G. Iliopoulos.
On convergence of importance sampling and other properly weighted
samples to the target distribution.
ArXiv Mathematics e-prints, ST(0505045), May 2005. [ bib | http ] |
| [32] |
A. M. Johansen, S. S. Singh, A. Doucet, and B.-N. Vo.
Convergence of the SMC implementation of the PHD filter.
Technical Report CUED/F-INFENG/TR-517, University of Cambridge,
Department of Engineering, Cambridge University Engineering Department,
Trumpington Street, Cambridge, CB2 1PZ, April 2005. [ bib | .djvu | .ps | .pdf ] |
| [33] |
P. Chigansky and R. Lipster.
What is always stable in nonlinear filtering.
ArXiv Mathematics e-prints, PR(0504094v1), April 2005. [ bib | http ] |
| [34] |
I. Gentil, B. Rémillard, and P. Del Moral.
Filtering of images for detecting multiple targets trajectories.
In Statistical Modeling and Analysis for Complex Data Problems.
Springer Verlag, April 2005. [ bib ] |
| [35] |
Thomas A. Down and Tim J. P. Hubbard.
NestedMICA: sensitive inference of over-represented motifs in
nucleic acid sequences.
Nucleic Acids Research, 33(5):1445-1453, March 2005. [ bib ] |
| [36] |
Ch. Skokos, K. E. Parsopoulos, P. A. Patsis, and M. N. Vrahatis.
Particle swarm optimization: An efficient method for tracing periodic
orbits in 3d galactic potentials.
ArXiv Mathematics e-prints, astro-ph(0502164v1), February
2005. [ bib | http ] |
| [37] |
Jodie Smith, David Onley, Caroline Garey, Stuart Crowther, Nicholas Cahir, Adam
Johansen, Sianie Painter, Grant Harradence, Ricardo Davis, and Peter
Swarbrick.
Determination of ANA specificity using the
UltraPlexxTM platform.
Annals of the New York Academy of Sciences, 1050:286-194,
2005. [ bib ] |
| [38] |
Jianjun Hu, Bin Li, and Daisuke Kihara.
Limitations and potentials of current motif discovery algorithms.
Nucleic Acids Research, 33(15):4899-1913, 2005. [ bib ] |
| [39] |
Simon Ian Hill and Arnaud Doucet.
A framework for kernel-based multi-category classification.
Technical Report CUED/F-INFENG/TR508, University of Cambridge,
Department of Engineering, Trumpington Street, Cambridge,CB1 2PZ, United
Kingdom, January 2005. [ bib | .pdf.gz ] |
| [40] |
Joseph F. Murray, Gordon F. Hughes, and Kennether Kreutz-Delgado.
Machine learning methods for predicting failures in hard drives: A
multiple-instance approach.
Journal of Machine Learning Research, 6:783-816, 2005. [ bib ] |
| [41] |
Uri Nodelman, Daphne Koller, and Christian R. Shelton.
Expectation propagation for continuous time Bayesian networks.
In Proceedings of the 21st international conference on
uncertainty in artificial intelligence, pages 431-440, 2005. [ bib | .pdf ] |
| [42] |
Uri Nodelman, Christopher R. Shelton, and Daphne Koller.
Expectation maximisation and complex duration distributions for
continuous time Bayesian networks.
In Proceedings of the 21st international conference on
uncertainty in artificial intelligence, pages 421-430, 2005. [ bib | .pdf ] |
| [43] |
K. B. Petersen and M. S. Pedersen.
The matrix cookbook, 2005.
Version 20050105. [ bib | http | .pdf ] |
| [44] |
Scott A. Sisson.
Trans-dimensional Markov chains: A decade of progress and future
perspectives.
Journal of the American Statistical Association, 2005.
To Appear. [ bib | .pdf ] |
| [45] |
E. Jacquier, M. Johannes, and N. Polson.
MCMC maximum likelihood for latent state models.
Journal of Econometrics, 2005.
To Appear. [ bib ] |
| [46] |
B. Jones, C. Carvalho, A. Dobra, C. Hans, C. Carter, and M. West.
Experiments in stochastic computation for high-dimensional graphical
models.
Statistical Science, 20(4), 2005. [ bib ] |
| [47] |
Daniel Edward Clark and Judith Bell.
Convergence results for the particle PHD filter.
IEEE Transactions on Signal Processing, 2005.
To Appear. [ bib ] |
| [48] |
Piotr Garbaczewski and Robert Olkiewicz.
Feynman-Kac kernels in Markovian representations of the
Schrödinger interpolating dynamics.
ArXiv Mathematics e-prints, quant-ph(9505012v2), January
2005. [ bib | http ] |
| [49] |
A. Lagnoux.
Rare event simulation.
Preprint, Laboratoire de Statistique et Probabilités,
Univeristé Paul Sabatier, 118, Route de Narbonne, 31062 Toulouse, Cedex
4, France, 2005.
To appear in PEIS. [ bib | .ps | .pdf ] |
| [50] |
J. Ching, S. K. Au, and J. L Beck.
Reliability estimation using dynamical systems subject to stochastic
excitation using subset simulation with splitting.
Computer Methods in Applied Mechanics and Engineering,
194:1557-1579, 2005. [ bib ] |
| [51] |
Maurice de Koning, Wei Cai, Babak Sadigh, Tomas Oppelstrup, Malvin H. Kalos,
and Vasily V. Bulatov.
Adaptive importance sampling Monte Carlo simulation of rare events.
Journal of Chemical Physics, 122(074103):1-12, 2005. [ bib | .pdf ] |
| [52] |
H. R. Künsch.
Recursive Monte Carlo filters: Algorithms and theoretical analysis.
Annals of Statistics, 33(5):1983-2021, 2005. [ bib ] |
| [53] |
Arnaud Doucet, P. Del Moral, and Gareth Peters.
Sequential Monte Carlo samplers.
In Adap'ski, Bormio, Italy, January 2005. IMS-ISBA.
MCMC'ski Satellite Meeting. [ bib ] |
| [54] |
R. Douc, A. Guillin, J.-M. Marin, and C. P. Robert.
Minimum variance importance sampling via Population Monte Carlo.
Preprint, CMAP / CEREMADE, 2005. [ bib | .pdf ] |
| [55] |
Jaroslav Krystul and Henk A. P. Blom.
Sequential Monte Carlo simulation of rare event probability in
stochastic hybrid systems.
In Proceedings of the 16th IFAC World Congress, 2005.
Preprint. [ bib | .pdf ] |
| [56] |
G. W. Peters.
Topics in sequential Monte Carlo samplers.
M.Sc. thesis, University of Cambridge, Department of Engineering,
January 2005. [ bib ] |
| [57] |
F. Cérou.
Limit theorems for the muiltilevel splitting algforithm in the
simulation of rare eents.
In M. E. Kuhl, N. M. Steiger, F. B. Armstrong, and J. A. Joines,
editors, Proceedings of the 2005 Winter Simulation Conference, 2005. [ bib | .pdf ] |
| [58] |
Y. Chen, J. Xie, and J. S. Liu.
Stopping-time resampling for sequential Monte Carlo methods.
Journal of the Royal Statistical Society B, 67:199-217, 2005. [ bib | .pdf ] |
| [59] |
P. Del Moral, A. Doucet, and A. Jasra.
Sequential Monte Carlo samplers (2005 revision).
Technical Report CUED/F-INFENG/TR-443, University of Cambridge,
Department of Engineering, 2005.
Revised version of a report from 2002. [ bib ] |
| [60] |
M. Klass, N. de Freitas, and A. Doucet.
Towards practical n2 Monte Carlo: The marginal particle filter.
In Proceedings of Uncertainty in Artificial Intelligence, 2005. [ bib ] |
| [61] |
H. P. Chan and T. L. Lai.
Importance sampling for generalized likelihood ratio procedures in
sequential analysis.
Sequential Analysis, 24:259-278, 2005. [ bib ] |
| [62] |
N. Chopin.
Central limit theorem for sequential Monte Carlo methods and its
applications to Bayesian inference.
Annals of Statistics, 32(6):2385-2411, December 2004. [ bib | .ps ] |
| [63] |
Pavel Chigansky.
On exponential stability of the nonlinear filter for slowly switching
Markov chains.
ArXiv Mathematics e-prints, (PR/0411596), November 2004. [ bib ] |
| [64] |
R. M. Neal.
Taking bigger metropolis steps by dragging fast variables.
Technical Report 0411, University of Toronto, Department of
Statistics, October 2004. [ bib | .ps ] |
| [65] |
Roberto Fernándex, Pablo A. Ferrari, and Gustavo R. Guerberoff.
Spatial birth-and-death proceses in random environment.
ArXiV Mathematics Reprints, (math.PR/0410191v1), October
2004. [ bib ] |
| [66] |
V. S. Borkar, S. Juneja, and A. A. Kherani.
Performance analysis conditioned on rare events: an adaptive
simulation scheme.
Communications in Information Systems, 3(4):259-278, September
2004. [ bib | .pdf ] |
| [67] |
Matthew P. Scarisbrick.
On the computer transcription of audio signals.
Ph.D. 1st year report, University of Cambridge, Department of
Engineering, August 2004. [ bib ] |
| [68] |
Stephen William Semmes.
A beginner's guide to analysis on metric spaces.
ArXiv Mathematics e-prints, (0408024v1), August 2004. [ bib ] |
| [69] |
W. Mueckenheim.
A severe inconsistency of transfinite set theory.
ArXiv Mathematics e-prints, August 2004. [ bib ] |
| [70] |
R. M. Neal.
Improving asymptotic variance of mcmc estimators: Non-reversible
chains are better.
Technical Report 0406, University of Toronto, Department of
Statistics, July 2004. [ bib | .ps ] |
| [71] |
Pieter-Tjerk de Boer, Dirk P. Kroese, Shie Mannor, and Reuven Y. Rubinstein.
A tutorial on the cross-entropy method.
Eprint 1187, University of Queensland, June 2004.
To appear in Annals of Operations Research. [ bib | .pdf ] |
| [72] |
Konstantinos E. Parsopoulos and Michael N. Vrahatis.
On the computation of all global minimizers through particle swarm
optimization.
IEEE Transactions on Evolutionary Computation, 8(3):211-224,
June 2004. [ bib | .pdf ] |
| [73] |
Firas Hamze and Nando de Freitas.
From fields to trees.
In WNAR/IMS Meeting, University of New Mexico, June 2004. [ bib ] |
| [74] |
Kevin McHale, Andrew J. Berglund, and Hideo Mabuchi.
Bayesian estimation for species identification in single-molecule
fluorescence microscopy.
Biophysical Journal, 86:3409-3422, June 2004. [ bib ] |
| [75] |
R. P. S. Mahler.
Random sets: Unification and computation for information fusion - a
retrospective assessment.
In 7th International Conference on Information Fusion,
Stockholm, Sweden, June 2004. [ bib | .pdf ] |
| [76] |
Jaroslav Krystul and Henk Blom.
Monte Carlo simulation of rare events in hybrid systems.
Report WP8.3, Hybridge, June 2004.
Version 0.6. [ bib ] |
| [77] |
Adam Michael Johansen, David Onley, Caroline Garey, and Jodie Hadley.
Bioassay reading system using a computer to locate and identify
microlabels by identifying spatially sequential groups or identification
codes.
Patent (Pending) GB 2395594, May 2004. [ bib | http ] |
| [78] |
John R. Hoffman and R. P. S. Mahler.
Multitarget miss distance via optimal assignment.
IEEE Transactions on Systems, Man and Cybernetics A,
34(3):327-336, May 2004. [ bib ] |
| [79] |
Ba-Ngu Vo, Sumeetpal Singh, and Wing Kin Ma.
Tracking multiple speakers using random sets.
In ICASSP, Montreal, Canada, May 2004.
To Appear. [ bib ] |
| [80] |
S. Sethuraman and S. R. S. Varadhan.
A martingale proof of Dobrushin's theorem for non-homogeneous
Markov chains.
ArXiv Mathematics e-prints, PR(0404231v1), April 2004. [ bib ] |
| [81] |
F. Le Glandand Nadia Oudjane.
Stability and uniform approximation of nonlinear filters using the
Hilbert metric amd application to particle filters.
The Annals of Applied Probability, 14(1):144-187, February
2004. [ bib | .pdf ] |
| [82] |
M. Doran and C. M. Müller.
Analyse this! a cosmological constraint package for cmbeasy.
ArXiv Mathematics e-prints, astro-ph(0311311v2), 2004. [ bib | http ] |
| [83] |
Olivier Bousquet, Ulrike von Luxburg, and Gunnar Rätsch, editors.
Advanced Lectures on Machine Learning, volume 3176.
Springer Verlag, Heidelberg, 2004. [ bib ] |
| [84] |
Søren Asmussen, Dirk P. Kroese, and Reuven Y. Rubinstein.
Heavy tails, importance sampling and cross-entropy.
Stochastic Models, 2004.
Submitted. [ bib | .ps ] |
| [85] |
Kumara Sastry, D. D. Johnson, David E. Goldberg, and Pascal Bellon.
Genetic programming for multi-timescale modelling.
International Journal of Multiscale compuitational Engineering,
2(2):239-256, 2004. [ bib | .pdf ] |
| [86] |
Inder Jeet Taneja and Pranesh Kumar.
Relative information of type s, Csizár's f-divergence, and
information inequaltiies.
Information Sciences, 166:105-125, 2004. [ bib ] |
| [87] |
Olivier Bousquet, Stépahne Boucheron, and Gábor Lugosi.
Introduction to statistical learning theory.
In Bousquet et al. [83], pages 169-207. [ bib ] |
| [88] |
Stépahne Boucheron, Gábor Lugosi, and Olivier Bousquet.
Concentration inequalities.
In Bousquet et al. [83], pages 208-240. [ bib ] |
| [89] |
Olivier Bousquet, Stépahne Boucheron, and Gábor Lugosi.
Theory of classification: A survery of recent advances.
ESAIM Probability and Statistics, 2004.
To Appear. [ bib | .pdf ] |
| [90] |
Ha Quang Minh and Thomas Hofmann.
Learning over compact metric spaces.
In Conference on Learning Theory, volume 17, 2004. [ bib | .pdf ] |
| [91] |
Zoubin Ghahramani.
Unsupervised learning.
In Bousquet et al. [83], pages 72-112. [ bib ] |
| [92] |
Léon Bottou.
Stochastic learning.
In Bousquet et al. [83], pages 146-168. [ bib ] |
| [93] |
Elad Yom-Tom.
An introduction to pattern classification.
In Bousquet et al. [83], pages 1-20. [ bib ] |
| [94] |
Christopher Burges.
Some notes on applied mathematics for machine learning.
In Bousquet et al. [83], pages 21-40. [ bib ] |
| [95] |
Michael Tipping.
Bayesian inference: An introduction to principles and practice in
machine learning.
In Bousquet et al. [83], pages 41-62. [ bib ] |
| [96] |
Carl Edward Rasmussen.
Gaussian processes in machine learning.
In Bousquet et al. [83], pages 63-71. [ bib ] |
| [97] |
Yves F. Atchade and Jun S. Liu.
The Wang-Landau algorithm for monte-carlo computation in general
state spaces.
Preprint, 2004. [ bib | .pdf ] |
| [98] |
O. Cappé, Arnaud Guillin, Jean-Michel Marin, and Christian P. Robert.
Population Monte Carlo.
Journal of Computational and Graphical Statistics,
13(4):907-929, 2004. [ bib ] |
| [99] |
Christophe Andrieu.
Monte Carlo methods for absolute beginners.
In Bousquet et al. [83], pages 113-145. [ bib ] |
| [100] |
Jonathan M. Keith, Dirk P. Kroese, and Darryn Bryant.
A generalised Markov sampler.
Methodology and Computing in Applied Probability, 6(1):29-35,
2004. [ bib | .pdf ] |
| [101] |
Hedibert Freitas Lopes and Mike West.
Bayesian model assessment in factor analysis.
Statistics Sinica, 14:41-67, 2004. [ bib ] |
| [102] |
R. P. S. Mahler.
statistics 101 for multisensor, multitarget data fusion.
IEEE Aerospance and Engineering Systems Magazine,
19(1):53-64, January 2004. [ bib ] |
| [103] |
Christian P. Robert.
Handbook of Computational Statistics, volume 1 Concepts and
Fundamentals, chapter III.ii Bayesian computational methods.
Springer Verlag, Heidelberg, 2004. [ bib | .pdf ] |
| [104] |
Ba-Ngu Vo and Wing Kin Ma.
Joint detection and tracking of multiple manouvering targets in
clutter using random finite sets.
In ICARCV2004, Kumming China, 2004.
To Appear. [ bib ] |
| [105] |
Matti Vihola.
Random Sets for Multitarget Tracking and Data Fusion.
Licentiate thesis, Tampere University of Technology, Department of
Engineering, 2004. [ bib | www: ] |
| [106] |
Kasper K. Berthelsen and Jesper Møller.
A Bayesian MCMC method for point process models with intractable
normalising constants.
In A. Baddeley, P. Gregori, J. Mateu, R. Stoica, and D. Stoyan,
editors, Spatial Point Process Modelling and its Applications, pages
7-15. 2004. [ bib | .ps ] |
| [107] |
Adrian Baddeley, R. Turner, J. Møller, and M. Hazelton.
Residual analysis for spatial point processes.
Research Report 2004/08, University of Western Austrlia, School of
Mathematics and Statistics, 35 Stirling Highway, CRAWLEY WA 6009, Australia,
2004. [ bib | .pdf ] |
| [108] |
Jorge Mateu and Miguel Montenegro.
Spatial Point Process Modelling and its Applications, chapter
On Kernel Estimators of Second-Order Measures for Spatial Point Processes,
pages 155-186.
Universitat Jaume I, 2004. [ bib | .pdf ] |
| [109] |
Patrizia Berti, Luca Pratelli, and Pietro Rigo.
Limit theorems for a class of identically distributed random
variables.
Annals of Probability, 32(3A):2029-2052, 2004.
Reprinted in ArXiv:math.PR/0410105. [ bib ] |
| [110] |
Sharad Goel.
Modified logarithmic Sobolev inequalities for some models of random
walk.
Stochastic Processes and their Applications, 114:51-79, 2004. [ bib | http ] |
| [111] |
Alexandfros Beskos, Omiros Papaspiliopoulos, and Gareth O. Roberts.
Retrospective exact simulatiopn of diffusion sample paths with
applications.
Submitted, 2004. [ bib | .pdf ] |
| [112] |
C. P. Robert and G. Casella.
Monte Carlo Statistical Methods.
Springer Verlag, New York, second edition, 2004. [ bib ] |
| [113] |
Y. Chen.
Another look at rejection sampling through importance sampling.
Working Paper 04-30, Institute of Statistics and Decision Sciences,
Duke University, Durhnam, NC 27708, USA, 2004. [ bib ] |
| [114] |
Paul Fearnhead and Loukia Meligoktisidou.
Exact filtering for partially observed continuous time models.
Journal of the Royal Statistical Society B, 66(3):771-789,
2004. [ bib ] |
| [115] |
Marco Lombardi and Simon J. Godsill.
On-line Bayesian estimation of AR signals in symmetric
α-stable boise.
Working Paper 2004-05, Dipartimento di Statistica, Università
degli Studi di Firenze, Viale Morgagni 59, 50134 Firenze, Italy, 2004. [ bib | .pdf ] |
| [116] |
Y. Chen.
Conditional inference on tables with structural zeros.
Discussion Report 04-26, Duke University, Instritute of Statistics
and Decisions Sciences, Durham, NC 27708, USA, 2004. [ bib | .html | .ps | .pdf ] |
| [117] |
N. Chopin.
Dynamical detection of change points in long time series.
Research Report 04:10, Bristol University, Statististics Group, 2004. [ bib | .pdf ] |
| [118] |
Pierre Del Moral, Arnaud Doucet, and Gareth W. Peters.
Sequential Monte Carlo samplers (2004 revision).
Technical Report CUED/F-INFENG/TR-443, University of Cambridge,
Department of Engineering, 2004. [ bib ] |
| [119] |
Arnaud Doucet and Stéphane Sénécal.
Fixed-lag sequential monte carlo.
In EURASIPCO, 2004. [ bib | .pdf ] |
| [120] |
Y. Chen and J. Liu.
Permanents, zero-one tables, and permutation tests.
Discussion Report 04-31, Duke University, Instritute of Statistics
and Decisions Sciences, Durham, NC 27708, USA, 2004. [ bib | .html | .ps | .pdf ] |
| [121] |
P. Del Moral, A. Doucet, and G. Peters.
Asymptotic and increasing propagation of chaos expansions for
genealogical particle models.
Proceedings of the LSP, 2004.
Submitted. [ bib ] |
| [122] |
P. Del Moral.
Feynman-Kac formulae: genealogical and interacting particle
systems with applications.
Probability and Its Applications. Springer Verlag, New York, 2004. [ bib ] |
| [123] |
Uri Nodelman and Eric Horvitz.
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