F. Abramovich, T. C. Bailey, and T. Sapatinas, Wavelet analysis and its statistical applications. The Statistician, pp.1-29, 2000.
DOI : 10.1111/1467-9884.00216

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.29.5736

F. Abramovich and Y. Benjamini, Thresholding of Wavelet Coefficients as Multiple Hypotheses Testing Procedure, Wavelets and Statistics Lecture Notes in Statistics 103, pp.5-14, 1995.
DOI : 10.1007/978-1-4612-2544-7_1

F. Abramovich and Y. Benjamini, Adaptive thresholding of wavelet coefficients, Computational Statistics & Data Analysis, vol.22, issue.4, 1996.
DOI : 10.1016/0167-9473(96)00003-5

F. Abramovich, P. Besbeas, and T. Sapatinas, Empirical Bayes approach to block wavelet function estimation, Computational Statistics & Data Analysis, vol.39, issue.4, 2000.
DOI : 10.1016/S0167-9473(01)00085-8

F. Abramovich and T. Sapatinas, Bayesian Approach to Wavelet Decomposition and Shrinkage, Bayesian Inference in Wavelet Based Models, 1999.
DOI : 10.1007/978-1-4612-0567-8_3

F. Abramovich and B. W. Silverman, Wavelet decomposition approaches to statistical inverse problems, Biometrika, vol.85, issue.1, pp.115-129, 1998.
DOI : 10.1093/biomet/85.1.115

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.3603

F. Abramovich, T. Sapatinas, and B. W. Silverman, Wavelet thresholding via a Bayesian approach, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.60, issue.4, pp.725-749, 1998.
DOI : 10.1111/1467-9868.00151

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.34.5975

F. Abramovich, Y. Benjamini, D. L. Donoho, and I. M. Johnstone, Adapting to unknown sparsity by controlling the false discovery rate, The Annals of Statistics, vol.34, issue.2, 2000.
DOI : 10.1214/009053606000000074

U. Amato and D. T. Vuza, Wavelet approximation of a function from samples affected by noise, Rev. Roumanie Math. Pure Appl, vol.42, pp.481-493, 1997.

C. Angelini, D. De-canditiis, and F. Leblanc, Wavelet regression estimation in nonparametric mixed effect models, Journal of Multivariate Analysis, vol.85, issue.2, 2000.
DOI : 10.1016/S0047-259X(02)00055-6

A. Antoniadis, Smoothing noisy data with tapered coiflets series, Scand. J. Statist, vol.23, pp.313-330, 1996.

A. Antoniadis, Wavelets in statistics: a review (with discussion), J. Ital. Statist. Soc, vol.103, pp.97-144, 1997.
DOI : 10.1007/978-1-4612-2544-7

A. Antoniadis and J. Fan, Regularization of wavelets approximations (with discussion), J. Am. Statist. Ass, p.96, 2001.

A. Antoniadis and G. Oppenheim, Wavelets and Statistics, Lect. Notes Statist, vol.103, 1995.
DOI : 10.1007/978-1-4612-2544-7

A. Antoniadis and D. T. Pham, Wavelet regression for random or irregular design, Computational Statistics & Data Analysis, vol.28, issue.4, pp.353-369, 1998.
DOI : 10.1016/S0167-9473(98)90145-1

Y. Benjamini and Y. Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, J. R. Statist. Soc. B, vol.57, pp.289-300, 1995.

J. Berger, Statistical Decision Theory and Bayesian Analysis, 1985.
DOI : 10.1007/978-1-4757-4286-2

L. Breiman and S. Peters, Comparing Automatic Smoothers (A Public Service Enterprise), International Statistical Review / Revue Internationale de Statistique, vol.60, issue.3, pp.271-290, 1992.
DOI : 10.2307/1403679

A. G. Bruce and H. Gao, Understanding WaveShrink: variance and bias estimation, Biometrika, vol.83, issue.4, pp.727-745, 1996.
DOI : 10.1093/biomet/83.4.727

J. B. Buckheit and D. L. Donoho, WaveLab and Reproducible Research, Wavelets and Statistics Lect. Notes Statist., 103, pp.55-81, 1995.
DOI : 10.1007/978-1-4612-2544-7_5

J. B. Buckheit, S. Chen, D. L. Donoho, I. M. Johnstone, and J. Scargle, About WaveLab, 1995.

C. S. Burrus, R. A. Gonipath, and H. Guo, Introduction to Wavelets and Wavelet Transforms: A Primer, 1998.

T. T. Cai, inequality approach, The Annals of Statistics, vol.27, issue.3, pp.898-924, 1999.
DOI : 10.1214/aos/1018031262

T. T. Cai and L. D. Brown, Wavelet shrinkage for nonequispaced samples, The Annals of Statistics, vol.26, issue.5, pp.1783-1799, 1998.
DOI : 10.1214/aos/1024691357

T. T. Cai and L. D. Brown, Wavelet estimation for samples with random uniform design, Statistics & Probability Letters, vol.42, issue.3, pp.313-321, 1999.
DOI : 10.1016/S0167-7152(98)00223-5

T. T. Cai and B. W. Silverman, Incorporating information on neighboring coefficients into wavelet estimation, p.63, 2001.

C. B. Chan, F. H. Chan, F. K. Lam, P. Lui, and P. W. Poon, Fast detection of venous air embolism in Doppler heart sound using the wavelet transform, IEEE Transactions on Biomedical Engineering, vol.44, issue.4, pp.237-246, 1997.
DOI : 10.1109/10.563293

H. A. Chipman, E. D. Kolaczyk, and R. E. Mcculloch, Adaptive Bayesian Wavelet Shrinkage, Journal of the American Statistical Association, vol.3, issue.440, pp.1413-1421, 1997.
DOI : 10.1080/01621459.1997.10473662

M. Clyde and E. I. George, Empirical Bayes Estimation in Wavelet Nonparametric Regression, Bayesian Inference in Wavelet Based Models, 1999.
DOI : 10.1007/978-1-4612-0567-8_19

M. Clyde and E. I. George, Flexible empirical Bayes estimation for wavelets, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.62, issue.4, pp.681-698, 2000.
DOI : 10.1111/1467-9868.00257

M. Clyde, G. Parmigiani, and B. Vidakovic, Multiple shrinkage and subset selection in wavelets, Biometrika, vol.85, issue.2, pp.391-401, 1998.
DOI : 10.1093/biomet/85.2.391

R. R. Coifman and D. L. Donoho, Translation-Invariant De-Noising, Wavelets and Statistics, pp.125-150, 1995.
DOI : 10.1007/978-1-4612-2544-7_9

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.125.3682

M. S. Crouse, R. D. Nowak, and R. G. Baraniuk, Wavelet-based statistical signal processing using hidden Markov models, IEEE Transactions on Signal Processing, vol.46, issue.4, pp.886-902, 1998.
DOI : 10.1109/78.668544

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.320.2336

B. Delyon and A. Juditsky, Estimating wavelet coefficients In Wavelets and Statistics, Lect. Notes Statist, vol.103, pp.15-168, 1995.

B. Delyon and A. Juditsky, On Minimax Wavelet Estimators, Applied and Computational Harmonic Analysis, vol.3, issue.3, pp.215-228, 1996.
DOI : 10.1006/acha.1996.0017

A. P. Dempster, N. M. Laird, and D. B. Rubin, Maximum likelihood from incomplete data via the EM algorithm (with discussion), J. R. Statist. Soc. B, vol.39, pp.1-38, 1977.

J. E. Dennis and H. H. Mei, Two new unconstrained optimization algorithms which use function and gradient values, Journal of Optimization Theory and Applications, vol.10, issue.4, pp.453-483, 1979.
DOI : 10.1007/BF00932218

D. L. Donoho and I. M. Johnstone, Ideal spatial adaptation by wavelet shrinkage, Biometrika, vol.81, issue.3, pp.425-455, 1994.
DOI : 10.1093/biomet/81.3.425

D. L. Donoho and I. M. Johnstone, Adapting to Unknown Smoothness via Wavelet Shrinkage, Journal of the American Statistical Association, vol.31, issue.432, pp.1200-1224, 1995.
DOI : 10.1080/01621459.1979.10481038

D. L. Donoho and I. M. Johnstone, Minimax estimation via wavelet shrinkage, The Annals of Statistics, vol.26, issue.3, pp.879-921, 1998.
DOI : 10.1214/aos/1024691081

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.161.9236

D. L. Donoho, I. M. Johnstone, G. Kerkyacharian, and D. Picard, Wavelet shrinkage: asymptopia? (with discussion), J. R. Statist. Soc. B, vol.57, pp.301-337, 1995.

S. Efromovich, Quasi-Linear Wavelet Estimation, Journal of the American Statistical Association, vol.6, issue.445, pp.189-204, 1999.
DOI : 10.1090/S0273-0979-1993-00390-2

S. Efromovich, Sharp linear and block shrinkage wavelet estimation, Statistics & Probability Letters, vol.49, issue.4, pp.323-329, 2000.
DOI : 10.1016/S0167-7152(00)00064-X

R. L. Eubank, Nonparametric Regression and Spline Smoothing, 1999.

J. Fan and I. Gijbels, Local Polynomial Modelling and its Applications, 1996.
DOI : 10.1007/978-1-4899-3150-4

G. Foster, Wavelets for period analysis of unevenly sampled time series, The Astronomical Journal, vol.112, pp.1709-1729, 1996.
DOI : 10.1086/118137

H. Gao and A. G. Bruce, WaveShrink with firm shrinkage, Statist. Sinica, vol.7, pp.855-874, 1997.

H. Gao, Wavelet shrinkage denoising using the non-negative garrote, J. Comp. Graph. Statist, vol.7, pp.469-488, 1998.

E. I. George and D. P. Foster, Calibration and empirical Bayes variable selection, Biometrika, vol.87, issue.4, 2000.
DOI : 10.1093/biomet/87.4.731

E. I. George and R. Mcculloch, Variable Selection via Gibbs Sampling, Journal of the American Statistical Association, vol.36, issue.423, pp.881-889, 1993.
DOI : 10.1007/BF01889985

P. J. Green and B. W. Silverman, Nonparametric regression and generalised linear models, 1994.

P. Hall, G. Kerkyacharian, and D. Picard, Block threshold rules for curve estimation using kernel and wavelet methods, The Annals of Statistics, vol.26, issue.3, pp.922-942, 1998.
DOI : 10.1214/aos/1024691082

P. Hall, G. Kerkyacharian, and D. Picard, On the minimax optimality of block thresholded wavelet estimators. rules for curve estimation using kernel and wavelet methods, Statist. Sinica, vol.9, pp.33-50, 1999.

P. Hall, S. Penev, G. Kerkyacharian, and D. Picard, Numerical performance of block thresholded wavelet estimators, Statistics and Computing, vol.7, issue.2, pp.115-124, 1997.
DOI : 10.1023/A:1018569615247

P. Hall and G. P. Nason, On choosing a non-integer resolution level when using wavelet methods, Statistics & Probability Letters, vol.34, issue.1, pp.5-11, 1997.
DOI : 10.1016/S0167-7152(96)00159-9

P. Hall and P. Patil, Effect of threshold rules on performance of wavelet-based curve estimators, Statist. Sinica, vol.6, pp.331-345, 1996.

P. Hall and P. Patil, On the choice of smoothing parameter, threshold and truncation in nonparametric regression by non-linear wavelet methods, J. R. Statist. Soc. B, vol.58, pp.361-377, 1996.

P. Hall and B. A. Turlach, Interpolation methods for nonlinear wavelet regression with irregularly spaced design, Ann. Statist, vol.25, pp.1912-1925, 1997.

W. Härdle, Applied Nonparametric Regression, 1990.

W. Härdle, G. Kerkyacharian, D. Pikard, and A. Tsybakov, Wavelets, Approximation, and Statistical Applications, Lecture Notes in Statistics, vol.129, 1998.

H. Huang and N. Cressie, Deterministic/Stochastic Wavelet Decomposition for Recovery of Signal From Noisy Data, Technometrics, vol.9, issue.3, pp.262-276, 2000.
DOI : 10.1214/aos/1176346060

S. Y. Huang and H. H. Lu, Bayesian wavelet shrinkage for nonparametric mixedeffects models, Statist. Sinica, vol.10, pp.1021-1040, 2000.

M. Jansen, M. Malfait, and A. Bultheel, Generalized cross validation for wavelet thresholding, Signal Processing, vol.56, issue.1, pp.33-44, 1997.
DOI : 10.1016/S0165-1684(97)83621-3

I. M. Johnstone, Minimax Bayes, asymptotic minimax and sparse wavelet priors In Statistical Decision Theory and Related Topics, pp.303-326, 1994.

I. M. Johnstone and B. W. Silverman, Wavelet Threshold Estimators for Data with Correlated Noise, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.59, issue.2, pp.319-351, 1997.
DOI : 10.1111/1467-9868.00071

I. M. Johnstone and B. W. Silverman, Empirical Bayes approaches to mixture problems and wavelet regression, 1998.

L. Khadra, A. S. Al-fahoum, and H. Nashash, Detection of life-threatening cardiac arrhythmias using the wavelet transformation, Medical & Biological Engineering & Computing, vol.37, issue.2, pp.626-632, 1997.
DOI : 10.1007/BF02510970

A. Kovac and B. W. Silverman, Extending the Scope of Wavelet Regression Methods by Coefficient-Dependent Thresholding, Journal of the American Statistical Association, vol.20, issue.449, pp.172-183, 2000.
DOI : 10.1111/1467-9868.00214

M. Lang, H. Guo, J. E. Odegard, C. S. Burrus, and R. O. Wells-jr, Noise reduction using an undecimated discrete wavelet transform, IEEE Signal Processing Letters, vol.3, issue.1, pp.10-12, 1996.
DOI : 10.1109/97.475823

S. T. Lin and P. D. Mcfadden, GEAR VIBRATION ANALYSIS BY B-SPLINE WAVELET-BASED LINEAR WAVELET TRANSFORM, Mechanical Systems and Signal Processing, vol.11, issue.4, pp.603-609, 1997.
DOI : 10.1006/mssp.1997.0097

S. G. Mallat, A theory for multiresolution signal decomposition: the wavelet representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.11, issue.7, pp.674-693, 1989.
DOI : 10.1109/34.192463

S. G. Mallat, A Wavelet Tour of Signal Processing, 1999.

J. S. Marron, S. Adak, I. M. Johnstone, M. H. Neumann, and P. Patil, Exact risk analysis of wavelet regression, J. Comp. Graph. Statist, vol.7, pp.278-309, 1998.

Y. Meyer, Wavelets and Operators, 1992.

M. Misiti, Y. Misiti, G. Oppenheim, and J. Poggi, Décomposition en ondelettes et méthodes comparatives : ´ etude d'une courbe de chargé eléctrique, 1994.

G. P. Nason, Wavelet regression by cross-validation, 1994.

G. P. Nason, Choice of the Threshold Parameter in Wavelet Function Estimation, Lect. Notes Statist, vol.103, pp.261-280, 1995.
DOI : 10.1007/978-1-4612-2544-7_16

G. P. Nason, Wavelet shrinkage using cross-validation, J. R. Statist. Soc. B, vol.58, pp.463-479, 1996.

G. P. Nason, Fast cross-validatory choice of wavelet smoothness, primary resolution and threshold in wavelet shrinkage using the Kovac-Silverman algorithm, 1999.

G. P. Nason and B. W. Silverman, The Stationary Wavelet Transform and some Statistical Applications, 1995.
DOI : 10.1007/978-1-4612-2544-7_17

M. H. Neumann and V. Spokoiny, On the efficiency of wavelet estimators under arbitrary error distributions, Math. Meth. Stat, vol.4, pp.137-166, 1995.

R. T. Ogden, Essential Wavelets for Statistical Applications and Data Analysis, 1997.
DOI : 10.1007/978-1-4612-0709-2

R. T. Ogden and E. Parzen, Change-point approach to data analytic wavelet thresholding, Statistics and Computing, vol.10, issue.2, pp.93-99, 1996.
DOI : 10.1007/BF00162519

R. T. Ogden and E. Parzen, Data dependent wavelet thresholding in nonparametric regression with change-point applications, Computational Statistics & Data Analysis, vol.22, issue.1, pp.53-70, 1996.
DOI : 10.1016/0167-9473(95)00041-0

D. B. Percival and A. T. Walden, Wavelet Methods for Time Series Analysis, 2000.

J. B. Ramsay, D. Usikov, and D. Zaslavsky, AN ANALYSIS OF U.S. STOCK PRICE BEHAVIOR USING WAVELETS, Fractals, vol.03, issue.02, pp.377-389, 1995.
DOI : 10.1142/S0218348X95000291

W. J. Staszewski and G. R. Tomlinson, Application of the wavelet transform to fault detection in a spur gear, Mechanical Systems and Signal Processing, vol.8, issue.3, pp.289-307, 1994.
DOI : 10.1006/mssp.1994.1022

C. Stein, Estimation of the Mean of a Multivariate Normal Distribution, The Annals of Statistics, vol.9, issue.6, pp.1135-1151, 1981.
DOI : 10.1214/aos/1176345632

G. Strang and T. Nguyen, Wavelets and Filter Banks, 1996.

R. Von-sachs and B. Macgibbon, Non-parametric curve estimation by wavelet thresholding with locally stationary errors. Scand, J. Statist, vol.27, pp.475-499, 2000.

M. Vannucci and F. Corradi, Covariance structure of wavelet coefficients: theory and models in a Bayesian perspective, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.61, issue.4, pp.971-986, 1999.
DOI : 10.1111/1467-9868.00214

B. Vidakovic, Nonlinear Wavelet Shrinkage with Bayes Rules and Bayes Factors, Journal of the American Statistical Association, vol.29, issue.441, pp.173-179, 1998.
DOI : 10.1080/01621459.1998.10474099

B. Vidakovic, Wavelet-Based Nonparametric Bayes Methods, Practical Nonparametric and Semiparametric Bayesian Statistics, 1998.
DOI : 10.1007/978-1-4612-1732-9_7

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.27.9693

B. Vidakovic, Statistical Modeling by Wavelets, 1999.
DOI : 10.1002/9780470317020

B. Vidakovic and F. Ruggeri, BAMS method: theory and simulations. Discussion Paper, Institute of Statistics and Decision Sciences, 2000.

G. Wahba, Spline Models for Observational Data, 1990.
DOI : 10.1137/1.9781611970128

Y. Wang, Function estimation via wavelet shrinkage for long-memory data, The Annals of Statistics, vol.24, issue.2, pp.466-484, 1996.
DOI : 10.1214/aos/1032894449

M. P. Wand and M. C. Jones, Kernel Smoothing, 1995.
DOI : 10.1007/978-1-4899-4493-1

N. Weyrich and G. T. Warhola, De-Noising Using Wavelets and Cross Validation, 1995.
DOI : 10.1007/978-94-015-8577-4_36

N. Weyrich and G. T. Warhola, Wavelet shrinkage and generalized cross-validation for de-noising with applications to speech, Approximation Theory VIII 2, pp.407-414, 1995.

P. Wojtaszczyk, A Mathematical Introduction to Wavelets, 1997.
DOI : 10.1017/CBO9780511623790