. Anstett-collin, . Mara, J. Denis-vidal, and . Goffart, UASA of complex models : Coping with dynamic and static inputs, 7th International Conference on Sensitivity Analysis of Model Output, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00926454

M. Bhandari, S. Shrestha, and J. New, Evaluation of weather datasets for building energy simulation, Energy and Buildings, vol.49, pp.109-118, 2012.
DOI : 10.1016/j.enbuild.2012.01.033

D. P. Bloomfield, An investigation into analytical and empirical validation techniques for dynamic thermal models of buildings, Internal report of BRE, 1988.

H. Breesch and . Janssens, Performance evaluation of passive cooling in office buildings based on uncertainty and sensitivity analysis, Solar Energy, vol.84, issue.8, pp.1453-1467, 2010.
DOI : 10.1016/j.solener.2010.05.008

A. L. Chan, Developing a modified typical meteorological year weather file for Hong Kong taking into account the urban heat island effect, Building and Environment, vol.46, issue.12, pp.2434-2441, 2011.
DOI : 10.1016/j.buildenv.2011.04.038

G. Chastaing, F. Gamboa, and C. Prieur, Generalized Hoeffding-Sobol decomposition for dependent variables - application to sensitivity analysis, Electronic Journal of Statistics, vol.6, issue.0, pp.2420-2448, 2012.
DOI : 10.1214/12-EJS749
URL : https://hal.archives-ouvertes.fr/hal-00649404

L. Chesné, T. Duforestel, J. Roux, and G. Rusaouën, Energy saving and environmental resources potentials: Toward new methods of building design, Building and Environment, vol.58, pp.199-207, 2012.
DOI : 10.1016/j.buildenv.2012.07.013

J. Clarke, P. Yaneske, and A. Pinney, The Harmonisation of Thermal Properties of Building Materials, BRE Publication BEPAC Research Report, vol.2, pp.1-87, 1990.

R. Confalonieri, Combining a weather generator and a standard sensitivity analysis method to quantify the relevance of weather variables on agrometeorological models inputs, Theoretical and Applied Climatology, pp.19-30, 1996.

B. Drury and . Crawley, Which Weather Data Should You Use for Energy Simulations of Commercial Buildings ?, ASHRAE Transactions, vol.104, issue.2, pp.1-18, 1998.

B. Drury, L. K. Crawley, F. C. Lawrie, W. F. Winkelmann, Y. J. Buhl et al., EnergyPlus : creating a new-generation building energy simulation program, Energy and Buildings, vol.33, issue.4, pp.319-331, 2001.

L. W. Crow, Weather year for energy calculations, ASHRAE Journal, vol.6, 1984.

P. De, W. , and W. Tian, Management of thermal performance risks in buildings subject to climate change, Building and Environment, vol.55, issue.0, pp.167-177, 2012.

M. Eames, T. Kershaw, and D. Coley, The appropriate spatial resolution of future weather files for building simulation, Journal of Building Performance Simulation, vol.5, issue.6, pp.347-358, 2012.
DOI : 10.1002/joc.1161

B. Efron and R. Tibshirani, Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical Accuracy, Statistical Science, vol.1, issue.1, pp.54-75, 1986.
DOI : 10.1214/ss/1177013815

J. M. Filkenstein and R. E. Schafer, Improved goodness to fit tests, Journal Biometrica, vol.58, 1971.

J. Goffart, E. Wurtz, G. Sauce, and T. Bejat, Impact and Source of Uncertainties in High Efficiency Building Simulation : Some Examples, Twelfth International IBPSA Conference Proceedings, pp.2822-2827, 2011.

A. Guaus, A. Bsaibes, T. Cartailler, C. Prieur, E. Lebon et al., Timedependent sensitivity and uncertainty analyses of an agroclimatic model for the water status management of vineyard, 7th International Conference on Sensitivity Analysis of Model Output, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01190046

G. Guyon, Role of the model user in results obtained from simulation software program, Building Simulation Conference, 1997.

F. Haldi and D. Robinson, The impact of occupants' behaviour on building energy demand, Journal of Building Performance Simulation, vol.77, issue.4, pp.323-338, 2011.
DOI : 10.1016/j.enbuild.2008.11.013

J. Helton and F. Davis, Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems, Reliability Engineering & System Safety, vol.81, issue.1, pp.23-691, 1996.
DOI : 10.1016/S0951-8320(03)00058-9

T. Hong, S. Chou, and T. Bong, Building simulation: an overview of developments and information sources, Building and Environment, vol.35, issue.4, pp.347-361, 2000.
DOI : 10.1016/S0360-1323(99)00023-2

C. J. Hopfe and J. L. Hensen, Uncertainty analysis in building performance simulation for design support, Energy and Buildings, vol.43, issue.10, pp.2798-2805, 2011.
DOI : 10.1016/j.enbuild.2011.06.034

S. P. Huang, S. T. Quek, and K. K. Phoon, Convergence study of the truncated Karhunen???Loeve expansion for simulation of stochastic processes, International Journal for Numerical Methods in Engineering, vol.8, issue.9, pp.1029-1043, 2001.
DOI : 10.1002/nme.255

R. Iman and W. Conover, A distribution-free approach to inducing rank correlation among input variables, Communications in Statistics - Simulation and Computation, vol.13, issue.4, pp.311-334, 1982.
DOI : 10.1080/00401706.1962.10490011

S. Ø. Jensen, Validation of building energy simulation programs: a methodology, Energy and Buildings, vol.22, issue.2, pp.133-144, 1995.
DOI : 10.1016/0378-7788(94)00910-C

F. Mark, P. A. Jentsch, L. James, A. S. Bourikas, and . Bahaj, Transforming existing weather data for worldwide locations to enable energy and building performance simulation under future climates, Renewable Energy, vol.55, pp.514-524, 2013.

F. Mark, A. S. Jentsch, P. A. Bahaj, and . James, Climate change future proofing of buildings.Generation and assessment of building simulation weather files, Energy and Buildings, vol.40, issue.12, pp.2148-2168, 2008.

R. D. Judkoff, Validation of building energy analysis simulation programs at the solar energy research institute, Energy and Buildings, vol.10, issue.3, pp.221-239, 1988.
DOI : 10.1016/0378-7788(88)90008-4

M. Kolokotroni, X. Ren, M. Davies, and A. Mavrogianni, London's urban heat island: Impact on current and future energy consumption in office buildings, Energy and Buildings, vol.47, pp.302-311, 2012.
DOI : 10.1016/j.enbuild.2011.12.019

J. Kreiss and E. Paparoditis, Bootstrap methods for dependent data: A review, Journal of the Korean Statistical Society, vol.40, issue.4, pp.357-378, 2011.
DOI : 10.1016/j.jkss.2011.08.009

S. Kucherenko, S. Tarantola, and P. Annoni, Estimation of global sensitivity indices for models with dependent variables, Computer Physics Communications, vol.183, issue.4, pp.937-946, 2012.
DOI : 10.1016/j.cpc.2011.12.020

H. Li, J. Harvey, and A. Kendall, Field measurement of albedo for different land cover materials and effects on thermal performance, Building and Environment, vol.59, issue.0, pp.536-546, 2013.
DOI : 10.1016/j.buildenv.2012.10.014

L. Lilburne and S. Tarantola, Sensitivity analysis of spatial models, International Journal of Geographical Information Science, vol.58, issue.2, pp.151-168, 2009.
DOI : 10.1016/j.ress.2005.11.048

I. Macdonald and P. Strachan, Practical application of uncertainty analysis, Energy and Buildings, vol.33, issue.3, pp.0-8, 2001.
DOI : 10.1016/S0378-7788(00)00085-2

T. Mara, Développement et Applications d'Outils d'Aide à la Vérification, la Calibration, l'Analyse de Sensibilité et d'Incertitude de Modèles, 2008.

T. Mara and O. Joseph, Comparison of some efficient methods to evaluate the main effect of computer model factors, Journal of Statistical Computation and Simulation, vol.1, issue.2, pp.167-178, 2008.
DOI : 10.1016/S0378-7788(00)00127-4
URL : https://hal.archives-ouvertes.fr/hal-01093033

E. A. Mohareb, C. A. Kennedy, L. D. Harvey, and K. D. Pressnail, Decoupling of building energy use and climate, Energy and Buildings, vol.43, issue.10, pp.2961-2963, 2011.
DOI : 10.1016/j.enbuild.2011.06.032

M. Vahid, A. S. Nik, and . Kalagasidis, Impact study of the climate change on the energy performance of the building stock in stockholm considering four climate uncertainties, Building and Environment, vol.60, pp.291-304, 2013.

M. Vahid, A. S. Nik, E. Kalagasidis, and . Kjellstrom, Statistical methods for assessing and analysing the building performance in respect to the future climate, Building and Environment, vol.53, pp.107-118, 2012.

E. Palomo, D. Barrio, and G. Guyon, Theoretical basis for empirical model validation using parameters space analysis tools, Energy and Buildings, vol.35, issue.10, pp.985-996, 2003.
DOI : 10.1016/S0378-7788(03)00038-0

E. Palomo and G. Guyon, Application of parameters space analysis tools for empirical model validation, Energy and Buildings, vol.36, issue.1, pp.23-33, 2004.
DOI : 10.1016/S0378-7788(03)00039-2

W. Parys, D. Saelens, and H. Hens, Coupling of dynamic building simulation with stochastic modelling of occupant behaviour in offices ??? a review-based integrated methodology, Journal of Building Performance Simulation, vol.4, issue.4, pp.339-358, 2011.
DOI : 10.1016/j.enbuild.2008.11.013

S. Patidar, D. P. Jenkins, G. J. Gibson, and P. F. Banfill, Analysis of probabilistic climate projections: heat wave, overheating and adaptation, Journal of Building Performance Simulation, vol.40, issue.4, pp.65-77, 2013.
DOI : 10.1038/416389a

K. Phoon, S. Huang, and S. Quek, Implementation of Karhunen???Loeve expansion for simulation using a wavelet-Galerkin scheme, Probabilistic Engineering Mechanics, vol.17, issue.3, pp.293-303, 2002.
DOI : 10.1016/S0266-8920(02)00013-9

K. Protassov, Analyse statistique des données expérimentales, EDP Sciences, 2008.

E. Mickael-rabouille, P. Wurtz, and . Perrotin, Analysis of dynamic thermal simulation for refurbishment, Thirteenth International IBPSA Conference Proceedings, 2013.

O. Roustant, Produits dérivés climatiques : aspects économétriques et financiers, 2003.

N. Saint-geours and C. Lavergne, Analyse de sensibilité globale d'un modèle spatialisé pour l'évaluation économique du risque d' inondation, Journal de la Société Française de Statistique, pp.49-71, 2011.

A. Saltelli, M. Ratto, S. Tarantola, and F. Camplongo, Update 1 of: Sensitivity Analysis for Chemical Models, Chemical Reviews, vol.112, issue.5, pp.1-21, 2012.
DOI : 10.1021/cr200301u

A. Saltelli and P. Annoni, How to avoid a perfunctory sensitivity analysis. Environmental Modelling and Software, pp.1508-1517, 2010.

A. Saltelli, P. Annoni, I. Azzini, F. Campolongo, M. Ratto et al., Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index, Computer Physics Communications, vol.181, issue.2, pp.259-270, 2010.
DOI : 10.1016/j.cpc.2009.09.018

A. Saltelli, M. Ratto, T. Andres, F. Campolongo, J. Cariboni et al., Introduction to Sensitivity Analysis, Global Sensitivity Analysis. The Primer, pp.1-51, 2008.
DOI : 10.1002/9780470725184.ch1

I. Sobol, . Tarantola, . Gatelli, W. Kucherenko, and . Mauntz, Estimating the approximation error when fixing unessential factors in global sensitivity analysis, Reliability Engineering & System Safety, vol.92, issue.7, pp.957-960, 2007.
DOI : 10.1016/j.ress.2006.07.001

I. M. Sobol, Sensitivity estimates for nonlinear mathematical models, Math. Mod. and Comput. Exp, vol.1, pp.407-414, 1993.

C. Spitz, Analyse de la fiabilité des outils de simulation et des incertitudes de métrologie appliquée à l' efficacité énergétique des bâtiments, 2012.

C. Spitz, L. Mora, E. Wurtz, and A. Jay, Practical application of uncertainty analysis and sensitivity analysis on an experimental house, Energy and Buildings, vol.55, pp.459-470, 2012.
DOI : 10.1016/j.enbuild.2012.08.013

B. Sudret, Global sensitivity analysis using polynomial chaos expansions, Reliability Engineering & System Safety, vol.93, issue.7, pp.964-979, 2008.
DOI : 10.1016/j.ress.2007.04.002
URL : https://hal.archives-ouvertes.fr/hal-01432217

J. Tanimoto, A. Hagishima, T. Iwai, and N. Ikegaya, Total utility demand prediction for multi-dwelling sites by a bottom-up approach considering variations of inhabitants??? behaviour schedules, Journal of Building Performance Simulation, vol.6, issue.1, pp.53-64, 2013.
DOI : 10.1016/j.apenergy.2009.11.006

W. Tian, A review of sensitivity analysis methods in building energy analysis. Renewable and Sustainable Energy Reviews, pp.411-419, 2013.

W. Tian and P. De-wilde, Uncertainty and sensitivity analysis of building performance using probabilistic climate projections: A UK case study, Automation in Construction, vol.20, issue.8, pp.1096-1109, 2011.
DOI : 10.1016/j.autcon.2011.04.011

M. Tr?ka and J. L. Hensen, Overview of HVAC system simulation, Automation in Construction, vol.19, issue.2, pp.93-99, 2010.
DOI : 10.1016/j.autcon.2009.11.019

L. Wang, P. Mathew, and X. Pang, Uncertainties in energy consumption introduced by building operations and weather for a medium-size office building, Energy and Buildings, vol.53, pp.152-158, 2012.
DOI : 10.1016/j.enbuild.2012.06.017