Team MISTIS

Members
Overall Objectives
Scientific Foundations
Application Domains
Software
New Results
Contracts and Grants with Industry
Other Grants and Activities
Dissemination
Bibliography
Inria / Raweb 2004
Team: MISTIS

Bibliography

Major publications by the team in recent years

[1]
G. Bouchard, S. Girard, A. Iouditski, A. Nazin.
Nonparametric Frontier estimation by linear programming, in: Automation and Remote Control, 2004, vol. 65, no 1, p. 58–64.
[2]
G. Celeux, S. Chrétien, F. Forbes, A. Mkhadri.
A Component-wise EM Algorithm for Mixtures, in: Journal of Computational and Graphical Statistics, 2001, vol. 10, p. 699–712.
[3]
G. Celeux, F. Forbes, N. Peyrard.
EM Procedures Using Mean Field-Like Approximations for Markov Model-Based Image Segmentation, in: Pattern Recognition, 2003, vol. 36, no 1, p. 131-144.
[4]
B. Chalmond, S. Girard.
Nonlinear modeling of scattered multivariate data and its application to shape change, in: IEEE Pattern Analysis and Machine Intelligence, 1999, vol. 21, no 5, p. 422–432.
[5]
P. Flandrin, P. Gonçalvès, P. Abry.
Lois d'échelle, Fractales et Ondelettes, Traité Information - Commande - Communication, Abry, P., Gonçalvès, P. and Lévy Véhel, J. eds, Paris, France, 2002, vol. 2, chap. Analyses en ondelettes et lois d'échelle.
[6]
F. Forbes, N. Peyrard.
Hidden Markov Random Field Model Selection Criteria based on Mean Field-like Approximations, in: in IEEE trans. PAMI, August 2003.
[7]
F. Forbes, A. E. Raftery.
Bayesian Morphology: Fast Unsupervised Bayesian Image analysis, in: Journal of the American Statistical Association, June 1999, vol. 94, no 446, p. 555-568.
[8]
S. Girard.
A nonlinear PCA based on manifold approximation, in: Computational Statistics, 2000, vol. 15(2), p. 145-167.
[9]
S. Girard.
A Hill type estimate of the Weibull tail-coefficient, in: Communication in Statistics - Theory and Methods, 2004, vol. 33, no 2, p. 205–234.
[10]
C. Robert.
Méthodes statistiques pour l'I.A. ; l'exemple du diagnostic médical, Masson, Paris, 1991.

Publications of the year

Articles in refereed journals and book chapters

[11]
G. Bouchard, S. Girard, A. Iouditski, A. Nazin.
Linear programming problems for frontier estimation, in: Applied Stochastic Models in Business and Industry, To appear, 2004.
[12]
L. Gardes, S. Girard.
Asymptotic properties of a Pickands type estimator of the extreme value index, in: Focus on probability theory, New-York, F. Colombus (editor), to appear, Nova Science, 2004.
[13]
L. Gardes, S. Girard.
Estimating extreme quantiles of Weibull tail-distributions, in: Communication in Statistics - Theory and Methods, to appear, 2004.
[14]
S. Girard.
On the asymptotic normality of the L1- error for Haar series estimates of Poisson point processes boundaries, in: Statistics and Probability Letters, 2004, vol. 66, p. 81–90.
[15]
S. Girard, P. Jacob.
Asymptotic normality of the L1-error for Geffroy's estimate of Poisson point process boundaries, in: Publications de l'Institut de Statistique de l'Université de Paris, to appear, 2004.
[16]
S. Girard, P. Jacob.
Extreme values and kernel estimates of point processes boundaries, in: ESAIM: Probability and Statistics, 2004, vol. 8, p. 150–168.
[17]
S. Girard, L. Menneteau.
Central limit theorems for smoothed extreme value estimates of point processes boundaries, in: Journal of Statistical Planning and Inference, to appear, 2004.
[18]
J. Jacques, C. Lavergne, N. Devictor.
Sensitivity Analysis in presence of model uncertainty and correlated inputs, in: Reliability Engineering and System Safety, To appear, 2004.

Internal Reports

[19]
F. Forbes, N. Peyrard, C. Fraley, D. Georgian-Smith, D. Goldhaber, A. E. Raftery.
Model-based Region of Interest Selection in Dynamic Breast MRI, Technical report, Stat. dept, Univ. of Washington, 2004, no 472.

Miscellaneous

[20]
C. Bouveyron, S. Girard, C. Schmid.
High Dimensional Discriminant Analysis, submitted for publication, 2004.
[21]
J. Diebolt, M. Garrido, S. Girard.
A goodness-of-fit test for the distribution tail, submitted for publication, 2004.
[22]
F. Forbes, J. Blanchet.
Markov Random Fields for Recognizing Textures modeled by Feature Vectors, submitted for publication, 2004.

References in notes

[23]
J. Diebolt, J. Ecarnot, M. Garrido, S. Girard, D. Lagrange.
Le logiciel Extremes, un outil pour l'étude des queues de distribution, in: La revue de Modulad, 2003, vol. 30, p. 53–60.
[24]
J. Diebolt, M. El-Aroui, M. Garrido, S. Girard.
Quasi-conjugate Bayes estimates for GPD parameters and application to heavy tails modelling, Technical report, INRIA, 2003, no RR-4803,
http://www.inria.fr/rrrt/rr-4803.html.
[25]
F. Forbes, N. Peyrard, C. Fraley, D. Georgian-Smith, D. Goldhaber, A. E. Raftery.
Region of interest selection and dynamic breast MRI data Analysis using multivariate statistical methods for Clustering and spatial segmentation, Technical report, Inria Rhone-Alpes, 2001, no RR-4249,
http://www.inria.fr/rrrt/rr-4249.html.
[26]
G. Fort, E. Moulines.
Convergence of the Monte-Carlo EM for curved exponential families, in: Annals of Statistics, 2003, vol. 31, no 4, p. 1220–1259.
[27]
L. Gardes.
Estimating the support of a Poisson process via the Faber-Shauder basis and extreme values, in: Publications de l'Institut de Statistique de l'Université de Paris, 2002, vol. XXXXVI, p. 43-72.
[28]
S. Girard, S. Iovleff.
Auto-Associative Models and Generalized Principal Component Analysis, in: Journal of Multivariate Analysis, 2005, vol. 93, no 1, p. 21–39.
[29]
S. Girard, P. Jacob.
Extreme values and Haar series estimates of point process boundaries, in: Scandinavian Journal of Statistics, 2003, vol. 30, no 2, p. 369–384.
[30]
S. Girard, P. Jacob.
Projection estimates of point processes boundaries, in: Journal of Statistical Planning and Inference, 2003, vol. 116, no 1, p. 1–15.
[31]
J. Zhang.
The Mean Field Theory in EM Procedures for Markov Random Fields, in: IEEE Trans. on signal processing, 1992, vol. 40, no 10, p. 2570–2583.

previous
next