A. Bibliographie1, A. Saidi, F. Ferraty, and R. Kassa, Single functional index model for a time series, p.321330, 2005.

A. Saidi, A. Ferraty, F. Kassa, R. Vieu, and P. , Cross-validated estimation in the single functional index model, Statistics, vol.42, p.475494, 2008.

A. Nze, P. Bühlmann, P. Doukhan, and P. , Functional estimation for mixing time series, C. Acad. Sci. Paris, vol.317, issue.405408, 1993.

A. Nze, P. Bühlmann, P. Doukhan, and P. , Weak dependence beyond mixing and asymptotics for nonparametric regression, The Annals of Statistics, vol.30, issue.2, 2002.
DOI : 10.1214/aos/1021379859
URL : http://projecteuclid.org/download/pdf_1/euclid.aos/1021379859

M. Attouch, A. Laksaci, and E. Ould-saïd, Asymptotic Distribution of Robust Estimator for Functional Nonparametric Models Communications in Statistics : Theory and Methods, p.13171335, 2010.

N. Azzedine, A. Laksaci, and E. Ould-saïd, On robust nonparametric regression estimation for a functional regressor, Statistics & Probability Letters, vol.78, issue.18, p.3221, 2008.
DOI : 10.1016/j.spl.2008.06.018
URL : https://hal.archives-ouvertes.fr/hal-00510975

L. Bagai and L. S. Prakasa-rao, Kernel-type density and failure rate estimation for associated sequences, Annals of the Institute of Statistical Mathematics, vol.26, issue.2, p.253266, 1995.
DOI : 10.1007/BF00773461

P. Billingsley, Probability and Measure, 1995.

T. Birkel, On the Convergence Rate in the Central Limit Theorem for Associated Processes, The Annals of Probability, vol.16, issue.4, p.16851698, 1988.
DOI : 10.1214/aop/1176991591

G. Boente and R. Fraiman, Robust nonparametric regression estimation, Journal of Multivariate Analysis, vol.29, issue.2, 1989.
DOI : 10.1016/0047-259X(89)90023-7

M. Bouraine, A. Saidi, A. Ferraty, and F. Vieu-ph, Choix optimal de l'indice multi-fonctionnel : Méthode de validation croisée, Rev. Roumaine de Math. Pures et Appliquées Vol, vol.55, issue.5, p.355367, 2010.

A. Bozorgnia, R. F. Patterson, and R. L. Taylor, Limit theorems for negatively dependent random variables, Proceedings of the First World Congress of Nonlinear Analysis, 1926.

A. V. Bulinski, On the convergence rates in the CLT for positively and negatively dependent random elds, Probability Theory and Mathematical Statistics, p.314, 1996.

A. Bulinski and C. Suquet, Normal approximation for quasi-associated random elds, Statist. Probab. Lett, vol.54, p.215226, 2001.

A. Bulinski and A. Shashkin, Limit theorems for associated random elds and related systems, 2007.

Z. W. Cai and G. G. Roussas, Weak convergence for smooth estimator of a distribution function under negative association, Stochastic Analysis and Applications, vol.15, issue.2, p.245268, 1999.
DOI : 10.1007/BF01192169

Z. W. Cai and G. G. Roussas, BerryEsseen bounds for a smooth estimate of a distribution function under association, J. Nonparametric Statist, vol.11, p.79106, 1999.

H. Cardot, F. Ferraty, and P. Sarda, Functional linear model, Statistics & Probability Letters, vol.45, issue.1, pp.45-1122, 1999.
DOI : 10.1016/S0167-7152(99)00036-X

H. Cardot, F. Ferraty, and P. Sarda, Spline Estimators for the Functional Linear Model, Statistica Sinica, vol.13, p.571591, 2003.

H. Cardot, F. Ferraty, and P. Sarda, Testing for no eect in functional linear regression models, some computational approaches, Comm. Statist. Simulation Comput, vol.33, p.171199, 2004.

H. Cardot, C. Crambes, and P. Sarda, Quantile regression when the covariates are functions, Journal of Nonparametric Statistics, vol.3, issue.7, p.541856, 2005.
DOI : 10.2307/1269656
URL : https://hal.archives-ouvertes.fr/hal-00134226

G. Collomb and W. Härdle, Strong uniform convergence rates in robust nonparametric time series analysis and prediction: Kernel regression estimation from dependent observations, Stoch. Proc. Appl. 23, p.7789, 1986.
DOI : 10.1016/0304-4149(86)90017-7

C. Crambes, L. Delsol, and A. Laksaci, Robust nonparametric estimation for functional data, Functional and Operatorial Statistics. Contribution to statistics, 2009.

D. Dabo-niang and G. Serge, Functional semiparametric partially linear model with autoregressive errors, Journal of Multivariate Analysis, vol.101, issue.2, p.307315, 2010.
DOI : 10.1016/j.jmva.2008.06.008
URL : https://hal.archives-ouvertes.fr/hal-00958112

M. Delecroix, W. Härdle, and M. Hristache, M-estimateurs semiparamétriques dans les modèles à direction révélatrice unique, Bull. Belg. Math. Soc. Simon Stevin, vol.6, issue.2, p.161185, 1999.

M. Delecroix, W. Härdle, and M. Hristache, Ecient estimation in conditional single-index regression, J. Multivariate Anal, vol.86, p.213226, 2003.

M. Delecroix and G. Geenens, A survey about single-index models theory, J. Statist. Plann. Inference, vol.1, issue.2, 2006.

M. Delecroix and G. Geenens, On semiparametric -estimation in single-index regression, Journal of Statistical Planning and Inference, vol.136, issue.3, p.730769, 2006.
DOI : 10.1016/j.jspi.2004.09.006
URL : https://hal.archives-ouvertes.fr/hal-00458962

L. Delsol, Régression non paramétrique fonctionnelle : Expression asymptotique des moments, Ann. I.S.U.P, vol.3, p.4367, 2007.

J. Dedecker and C. Prieur, Coupling for ?-Dependent Sequences and Applications, Journal of Theoretical Probability, vol.3, issue.4, pp.861-885, 2004.
DOI : 10.1007/s10959-004-0578-x

J. Dedecker, P. Doukhan, G. Lang, R. León, J. R. Louhichi et al., Weak dependence, Lecture Notes in Statistics, 2007.
DOI : 10.1007/978-0-387-69952-3_2
URL : https://hal.archives-ouvertes.fr/hal-00686031

J. Dedecker and C. Prieur, Coupling for ?-Dependent Sequences and Applications, Journal of Theoretical Probability, vol.3, issue.4, pp.861-885, 2004.
DOI : 10.1007/s10959-004-0578-x

P. Doukhan, Mixing : Properties and Examples., Lecture Notes in Sta- tistics, 1994.

P. Doukhan and S. Louhichi, A new weak dependence condition and applications to moment inequalities, Stochastic Processes and their Applications, vol.84, issue.2, p.313342, 1999.
DOI : 10.1016/S0304-4149(99)00055-1

J. Esary, F. Proschan, and D. Walkup, Association of Random Variables, with Applications, The Annals of Mathematical Statistics, vol.38, issue.5, p.14661476, 1967.
DOI : 10.1214/aoms/1177698701

M. Ezzahrioui, O. Saïd, and E. , Some asymptotic results of a nonparametric conditional mode estimator for functional time series data, Statist. Neerlandica, vol.64, issue.2, p.171201, 2010.

F. Ferraty, A. Peuch, and P. Vieu, Mod??le ?? indice fonctionnel simple, Comptes Rendus Mathematique, vol.336, issue.12, 2003.
DOI : 10.1016/S1631-073X(03)00239-5

F. Ferraty and P. Vieu, Nonparametric functional data analysis : Theory and Practice, 2006.

F. Ferraty, A. Mas, and P. Vieu, Advances in nonparametric regression for functional variables. Aust. and New Zeal, J. of Statist, vol.49, pp.1-20, 2007.

F. Ferraty, A. Laksaci, and P. Vieu, Estimating Some Characteristics of the Conditional Distribution in Nonparametric Functional Models, Statist. Inf. for Stoch. Proc. 9, p.4776, 2006.
DOI : 10.1007/s11203-004-3561-3

F. Ferraty, A. Laksaci, A. Tadj, and P. Vieu, Rate of uniform consistency for nonparametric estimates with functional variables, Journal of Statistical Planning and Inference, vol.140, issue.2, p.335352, 2009.
DOI : 10.1016/j.jspi.2009.07.019
URL : https://hal.archives-ouvertes.fr/hal-00629617

F. Ferraty, J. Park, and P. Vieu, Functional average derivative regression, 2011.

F. Ferraty, J. Park, and P. Vieu, Estimation of a Functional Single Index Model, 2011.
DOI : 10.1007/978-3-7908-2736-1_17
URL : https://hal.archives-ouvertes.fr/hal-00794772

L. Ferré, J. Dauxois, and A. F. Yao, Un modèle semi-paramétrique pour variables aléatoires hilbertiennes (in french), C. R. Acad. Sci. Paris Série. I Math, vol.333, issue.10, p.947952, 2001.

C. Fortuyn, P. Kastelyn, and J. Ginibre, Correlation inequalities on some partially ordered sets, Communications in Mathematical Physics, vol.26, issue.Suppl., p.119127, 1971.
DOI : 10.1007/BF01651330

R. Kallabis and M. H. Neumann, An exponential inequality under weak dependence, Bernoulli, vol.12, issue.2, p.333350, 2006.
DOI : 10.3150/bj/1145993977

P. Hall, On Projection Pursuit Regression, The Annals of Statistics, vol.17, issue.2, pp.573-588, 1989.
DOI : 10.1214/aos/1176347126

P. Hall, H. G. Müller, and F. Yao, Estimation of functional derivatives, The Annals of Statistics, vol.37, issue.6A, 2009.
DOI : 10.1214/09-AOS686

W. Härdle and A. Tsybakov, Robust Nonparametric Regression with Simultaneous Scale Curve Estimation, The Annals of Statistics, vol.16, issue.1, p.120135, 1988.
DOI : 10.1214/aos/1176350694

W. Härdle, P. Hall, and H. Ichumira, Optimal Smoothing in Single-Index Models, The Annals of Statistics, vol.21, issue.1, p.157178, 1993.
DOI : 10.1214/aos/1176349020

T. E. Harris, A lower bound for the critical probability in a certain percolation process, Proc. Cambridge Philos. Soci. 56, 1320.
DOI : 10.1214/aoms/1177706894

M. Hristache, A. Juditsky, and V. Spokoiny, Direct estimation of the index coecient in the single-index model, Ann. Statist, vol.29, p.595623, 2001.

P. J. Huber, Robust estimation of a location parameter, Ann. Math. Statist, vol.35, p.73101, 1964.

P. J. Huber, Projection Pursuit, The Annals of Statistics, vol.13, issue.2, p.435475, 1985.
DOI : 10.1214/aos/1176349519

K. Jong-dev and F. Proschan, Negative association of random variables, with applications, Ann. Statist, vol.11, 1983.

E. L. Lehmann, Some concepts of dependence, Ann. Math. Statist, vol.37, p.11371153, 1966.

E. Leibscher, ESTIMATION OF THE DENSITY AND THE REGRESSION FUNCTION UNDER MIXING CONDITIONS, Statistics & Risk Modeling, vol.19, issue.1, p.926, 2001.
DOI : 10.1524/strm.2001.19.1.9

W. V. Li and Q. M. Shao, Gaussian processes: Inequalities, small ball probabilities and applications, Stochastic processes : Theory and Methods
DOI : 10.1016/S0169-7161(01)19019-X
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.146.3738

E. Masry, Recursive probability density estimation for weakly dependent stationary processes IEEE, Trans. Inform. Theory, vol.32, p.254267, 1986.

E. Masry, Multivariate probability density estimation for associated processes: strong consistency and rates, Statistics & Probability Letters, vol.58, issue.2, 2002.
DOI : 10.1016/S0167-7152(02)00105-0

W. K. Newey and T. M. Stoker, Eciency of weighted average derivative estimators and index models, Econometrica, vol.61, issue.2, p.11991223, 1993.

C. M. Newman, Normal uctuations and the FKG inequalities, Comm. Math. Phys, vol.74, issue.2, p.119128, 1980.

C. M. Newman, Asymptotic independence and limit theorems for positively and negatively dependent random variables, IMS Lect. NotesMonographs Series, vol.5, p.127140, 1984.
DOI : 10.1214/lnms/1215465639

R. F. Patterson and R. L. Taylor, Strong laws of large numbers for negatively dependent random elements, Nonlinear Analysis: Theory, Methods & Applications, vol.30, issue.7, p.42294235, 1997.
DOI : 10.1016/S0362-546X(97)00279-4

J. O. Ramsay, When the data are functions, Psychometrika, vol.47, issue.4, p.396, 1982.
DOI : 10.1007/BF02293704

J. Ramsay and C. Dalzell, Some tools for functional data analysis, J. R. Statist. Soc. B, vol.53, issue.539572, 1991.

J. Ramsay and B. W. Silverman, Functional data analysis, 1997.

J. Ramsay and B. W. Silverman, Applied functional data analysis : Methode and Case Studies, 2002.
DOI : 10.1007/b98886

J. Ramsay and B. W. Silverman, Functional data analysis, 2005.

E. Rio, Théorie asymptotique des processus aléatoires faiblement dépendants, p.31, 2000.

G. G. Roussas, Kernel estimates under association: strong uniform consistency, Statistics & Probability Letters, vol.12, issue.5, p.215224, 1991.
DOI : 10.1016/0167-7152(91)90028-P

G. G. Roussas, Asymptotic normality of random elds of positively or negatively associated processes, J of Multivar. Analys, vol.50, p.152173, 1994.

G. G. Roussas, Positive and negative dependence with some statistical applications, Asymptotics, Nonparametrics and Time Series, p.757788, 1999.

G. G. Roussas, Prediction Under Association, Recent Advances in Reliability Theory : Methodology, Practice and Inference. BirkhSauser, 2000.
DOI : 10.1007/978-1-4612-1384-0_29

G. G. Roussas, Fixed design regression under association, Lecture Notes- Monograph Series, p.7189, 2001.

R. Sering, Approximation Theorems of Mathematical Statistics, 1980.

R. P. Sherman, Maximal Inequalities for Degenerate $U$-Processes with Applications to Optimization Estimators, The Annals of Statistics, vol.22, issue.1, p.439459, 1994.
DOI : 10.1214/aos/1176325377

R. L. Taylor, R. F. Patterson, and A. Bozorgnia, Weak laws of large numbers for arrays of rowwise negatively dependent random variables, Journal of Applied Mathematics and Stochastic Analysis, vol.14, issue.3, p.227236, 2001.
DOI : 10.1155/S1048953301000181

R. L. Taylor, R. F. Patterson, and A. Bozorgnia, A strong law of large numbers for arrays of rowwise negatively dependent random variables, p.643656, 2002.

X. Xia, . Tong, and W. K. Li, On extended partially linear single-index models, Biometrika, vol.86, issue.4, p.831842, 1999.
DOI : 10.1093/biomet/86.4.831

X. Xia and W. K. Li, On the estimation and testing of functional-coecient linear models, Stat. Sinica, vol.9, p.735757, 1999.

X. Xia and H. Z. An, Projection Pursuit Autoregression in Time Series, Journal of Time Series Analysis, vol.20, issue.6, 2002.
DOI : 10.1111/1467-9892.00167

E. Youndjé, Estimation non paramétrique de la densité conditionnelle par la méthode du noyau, Thèse de Doctorat, 1993.

C. 2. Single, . I. Index-model:-i, A. Process-case-bibliographie-aït-saidi, F. Ferraty, and R. Kassa, Single functional index model for a time series, p.321330, 2005.

A. Saidi, A. Ferraty, F. Kassa, R. Vieu, and P. , Cross-validated estimation in the single functional index model, Statistics, vol.42, p.475494, 2008.

M. Delecroix, W. Härdle, and M. Hristache, Ecient estimation in conditional single-index regression, J. Multivariate Anal, vol.86, p.213226, 2003.

M. Ezzahrioui, O. Saïd, and E. , Some asymptotic results of a nonparametric conditional mode estimator for functional time series data, 2010.

F. Ferraty, A. Peuch, and P. Vieu, Mod??le ?? indice fonctionnel simple, Comptes Rendus Mathematique, vol.336, issue.12, 2003.
DOI : 10.1016/S1631-073X(03)00239-5

F. Ferraty and P. Vieu, NonParametric Functional Data Analysis : Theory and Practice, 2006.

W. Härdle, P. Hall, and H. Ichumira, Optimal Smoothing in Single-Index Models, The Annals of Statistics, vol.21, issue.1, p.157178, 1993.
DOI : 10.1214/aos/1176349020

M. Hristache, A. Juditsky, and V. Spokoiny, Direct estimation of the index coecient in the single-index model, Ann. Statist, vol.29, p.595623, 2001.

A. Laksaci, M. Lemdani, O. Saïd, and E. , A generalized -approach for a kernel estimator of conditional quantile with functional regressors: Consistency and asymptotic normality, Statistics & Probability Letters, vol.79, issue.8, 2009.
DOI : 10.1016/j.spl.2008.12.016
URL : https://hal.archives-ouvertes.fr/hal-00516884

A. Saidi, A. Ferraty, F. Kassa, and R. , Cross-validated estimation in the single functional index model, Statistics, vol.42, p.475494, 2008.

A. Nze, P. Bühlmann, P. Doukhan, and P. , Weak dependence beyond mixing and asymptotics for non parametric regression, Ann. Statist, vol.397, pp.30-32, 2002.
DOI : 10.1214/aos/1021379859
URL : http://projecteuclid.org/download/pdf_1/euclid.aos/1021379859

S. Attaoui, A. Laksaci, and E. Ould-saïd, A note on the conditional density estimate in the single functional index model, Statistics & Probability Letters, vol.81, issue.1, p.4553, 2011.
DOI : 10.1016/j.spl.2010.09.017
URL : https://hal.archives-ouvertes.fr/hal-00698847

A. Bulinski and C. Suquet, Normal approximation for quasi-associated random elds, Statist. Probab. Lett, vol.54, p.215226, 2001.

A. Bulinski and E. Shabanovich, Asymptotical behaviour of some functionals of positively and negatively dependent random elds Fundam, 1998.

M. Delecroix, W. Härdle, and M. Hristache, Ecient estimation in conditional single-index regression, J. Multivariate Anal, vol.86, p.213226, 2003.

J. L. Doob, Stochastic Processes, 1953.

L. Douge, Théorèmes limites pour des variables quasi-associées hilbertiennes, Ann. I.S.U.P, vol.54, p.5160, 2010.

J. Esary, F. Proschan, and D. Walkup, Association of Random Variables, with Applications, The Annals of Mathematical Statistics, vol.38, issue.5, p.14661476, 1967.
DOI : 10.1214/aoms/1177698701

F. Ferraty, A. Peuch, and P. Vieu, Mod??le ?? indice fonctionnel simple, Comptes Rendus Mathematique, vol.336, issue.12, 2003.
DOI : 10.1016/S1631-073X(03)00239-5

F. Ferraty, A. Mas, and P. Vieu, Advances in nonparametric regression for functional variables. Aust. and New Zeal, J. of Statist, vol.49, pp.1-20, 2007.

F. Ferraty, J. Park, and P. Vieu, Estimation of a Functional Single Index Model, Recent advences in functional data analysis and related topics. Contribution to statistics. Physica, 2011.
DOI : 10.1007/978-3-7908-2736-1_17
URL : https://hal.archives-ouvertes.fr/hal-00794772

T. Gasser, P. Hall, and B. Presnell, Nonparametric estimation of the mode of a distribution of random curves, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.60, issue.4, p.681691, 1998.
DOI : 10.1111/1467-9868.00148

W. Härdle, P. Hall, and H. Ichimura, Optimal Smoothing in Single-Index Models, The Annals of Statistics, vol.21, issue.1, pp.157-178, 1993.
DOI : 10.1214/aos/1176349020

J. Horowitz and W. Härdle, Direct Semiparametric Estimation of Single-Index Models with Discrete Covariates, Journal of the American Statistical Association, vol.56, issue.436, p.16321641, 1996.
DOI : 10.2307/2951780

M. Hristache, A. Juditsky, and V. Spokoiny, Direct estimation of the index coecient in the single-index model, Ann. Statist, vol.29, p.595623, 2001.

K. Jong-dev and F. Proschan, Negative association of random variables, with applications, Ann. Statist, vol.11, 1983.

R. Kallabis and M. H. Neumann, An exponential inequality under weak dependence, Bernoulli, vol.12, issue.2, p.333350, 2006.
DOI : 10.3150/bj/1145993977

E. Masry, Nonparametric regression estimation for dependent functional data: asymptotic normality, Stochastic Processes and their Applications, vol.115, issue.1, p.155177, 2005.
DOI : 10.1016/j.spa.2004.07.006

P. Matula, A note on the almost sure convergence of sums of negatively dependent random variables, Statistics & Probability Letters, vol.15, issue.3, 1992.
DOI : 10.1016/0167-7152(92)90191-7

C. M. Newman, Asymptotic independence and limit theorems for positively and negatively dependent random variables, Inequalities in Statistics and Probability, p.127140, 1984.
DOI : 10.1214/lnms/1215465639

L. Pitt, Positively Correlated Normal Variables are Associated, The Annals of Probability, vol.10, issue.2, p.496499, 1982.
DOI : 10.1214/aop/1176993872
URL : http://projecteuclid.org/download/pdf_1/euclid.aop/1176993872

G. G. Roussas, Positive and negative dependence with some statistical applications, p.757788, 1999.

G. G. Roussas, Prediction Under Association, Recent Advances in Reliability Theory : Methodology, Practice and Inference. BirkhSauser, 2000.
DOI : 10.1007/978-1-4612-1384-0_29

A. Shashkin, Quasi-association for system of Gaussian vectors, 2002.

A. Nze, P. Bühlmann, P. Doukhan, and P. , Functional estimation for mixing time series, C. Acad. Sci. Paris, vol.317, issue.405408, 1993.

R. E. Barlow and F. Proschan, Statistical Theory of Reliability and Life Testing. Probability Models, 1981.

G. Boente and R. Fraiman, Robust nonparametric regression estimation, Journal of Multivariate Analysis, vol.29, issue.2, 1989.
DOI : 10.1016/0047-259X(89)90023-7

D. Bosq, Nonparametric statistics for stochastic process : Estimation and prediction, 1998.

D. Bosq and D. Blanke, Inference and prediction in large dimensions, 2007.
DOI : 10.1002/9780470724033

A. Bulinski and E. Shabanovich, Asymptotical behaviour of some functionals of positively and negatively dependent random elds. (in Russian), Fundam. Appl. Math, vol.4, p.479492, 1998.

A. Bulinski and C. Suquet, Normal approximation for quasi-associated random elds, Statist. Probab. Lett, vol.54, p.215226, 2001.

A. Bulinski and A. Shashkin, Limit theorems for associated random elds and related systems, 2007.

J. Dedecker and C. Prieur, Coupling for ?-Dependent Sequences and Applications, Journal of Theoretical Probability, vol.3, issue.4, pp.861-885, 2004.
DOI : 10.1007/s10959-004-0578-x

J. Esary, F. Proschan, and D. Walkup, Association of Random Variables, with Applications, The Annals of Mathematical Statistics, vol.38, issue.5, p.14661476, 1967.
DOI : 10.1214/aoms/1177698701

J. Fan and I. Gijbels, Local Polynomial Modeling and its Applications, 1996.

L. Györ, W. Härdle, P. Sarda, and P. Vieu, Nonparametric curve estimation from time series, Lecture Notes in Statistics, vol.60, 1989.

W. Härdle and A. Tsybakov, Robust Nonparametric Regression with Simultaneous Scale Curve Estimation, The Annals of Statistics, vol.16, issue.1, p.120135, 1988.
DOI : 10.1214/aos/1176350694

P. Huber, Robust Estimation of a Location Parameter, Ann. Math. Statist, vol.35, p.73101, 1964.

K. Jong-dev and F. Proschan, Negative association of random variables, with applications, Ann. Statist, vol.11, 1983.

R. Kallabis and M. H. Neumann, An exponential inequality under weak dependence, Bernoulli, vol.12, issue.2, p.333350, 2006.
DOI : 10.3150/bj/1145993977

E. Leibscher, ESTIMATION OF THE DENSITY AND THE REGRESSION FUNCTION UNDER MIXING CONDITIONS, Statistics & Risk Modeling, vol.19, issue.1, p.926, 2001.
DOI : 10.1524/strm.2001.19.1.9

Y. P. Mack and B. W. Silverman, Weak and strong uniform consistency of kernel regression estimates, Zeitschrift f???r Wahrscheinlichkeitstheorie und Verwandte Gebiete, vol.26, issue.No. 2, pp.61-105115, 1992.
DOI : 10.1007/BF00539840

E. Masry, Recursive probability density estimation for weakly dependent stationary processes IEEE, Trans. Inform. Theory, vol.32, p.254267, 1986.

G. G. Roussas, Kernel estimates under association: strong uniform consistency, Statistics & Probability Letters, vol.12, issue.5, p.215224, 1991.
DOI : 10.1016/0167-7152(91)90028-P

G. G. Roussas, Curve estimation in random elds of associated processes, J. Nonparametric Statist, vol.2, p.215224, 1993.

G. G. Roussas, Prediction Under Association, Recent Advances in Reliability Theory : Methodology, Practice and Inference. BirkhSauser, 2000.
DOI : 10.1007/978-1-4612-1384-0_29

A. Shashkin, Quasi-association for system of Gaussian vectors, 2002.