T. Berthou, P. Stabat, R. Salvazet, and D. Marchio, Development and validation of a gray box model to predict thermal behavior of occupied office buildings, Energy and Buildings, vol.74, pp.91-100, 2014.
DOI : 10.1016/j.enbuild.2014.01.038

URL : https://hal.archives-ouvertes.fr/hal-01299414

M. Jiménez, H. Madsen, and K. K. Andersen, Identification of the main thermal characteristics of building components using MATLAB, Building and Environment, vol.43, issue.2, pp.170-180, 2008.
DOI : 10.1016/j.buildenv.2006.10.030

P. Malisani, F. Chaplais, N. Petit, and D. Feldmann, Thermal building model identification using time-scaled identification methods, 49th IEEE Conference on Decision and Control (CDC), pp.308-315, 2010.
DOI : 10.1109/CDC.2010.5717975

URL : https://hal.archives-ouvertes.fr/hal-00549032

I. Hazyuk, C. Ghiaus, and D. Penhouet, Optimal temperature control of intermittently heated buildings using Model Predictive Control: Part I ??? Building modeling, Building and Environment, vol.51, pp.379-387, 2012.
DOI : 10.1016/j.buildenv.2011.11.009

URL : https://hal.archives-ouvertes.fr/hal-00732243

I. Naveros, P. Bacher, D. Ruiz, M. Jiménez, and H. Madsen, Setting up and validating a complex model for a simple homogeneous wall, Energy and Buildings, vol.70, pp.303-317, 2014.
DOI : 10.1016/j.enbuild.2013.11.076

C. Zayane, Identification d'un modèle de comportement thermique de bâtimentbâtiment`bâtimentà partir de sa courbe de charge, 2011.

C. F. Van-loan, Computing integrals involving the matrix exponential, IEEE Transactions on Automatic Control, vol.23, issue.3, pp.395-404, 1978.
DOI : 10.1109/TAC.1978.1101743

A. P. Dempster, N. M. Laird, and D. B. Rubin, Maximum likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society. Series B, pp.1-38, 1977.

R. H. Shumway, D. S. Stoffer, R. Douc, ´. E. Moulines, and D. Stoffer, An approach to time series smoothing and forecasting using the EM algorithm Journal of time series analysis Nonlinear time series: Theory, Methods and Applications with R examples, pp.253-264, 1982.

E. L. Lehmann and G. Casella, Theory of point estimation, ser. Springer texts in statistics, 1998.

R. A. Fisher, Theory of Statistical Estimation, Mathematical Proceedings of the Cambridge Philosophical Society, pp.700-725, 1925.
DOI : 10.1017/S0305004100009580

M. Segal and E. Weinstein, A new method for evaluating the log-likelihood gradient, the Hessian, and the Fisher information matrix for linear dynamic systems, IEEE Transactions on Information Theory, vol.35, issue.3, pp.682-687, 1989.
DOI : 10.1109/18.30995

L. Ljung, System identification: theory for the user, 1987.