D. Aldous and J. A. , Reversible markov chains and random walks on graphs Unfinished monograph, recompiled 2014, 2002.
DOI : 10.1007/bf01048272

K. Avrachenkov, A. Kadavankandy, L. O. Prokhorenkova, and A. Raigorodskii, Pagerank in undirected random graphs, WAW, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01227383

K. Avrachenkov, N. Litvak, M. Sokol, and D. Towsley, Quick Detection of Nodes with Large Degrees, Internet Mathematics, vol.10, issue.1-2, pp.1-19, 2014.
DOI : 10.1080/15427951.2013.798601
URL : https://hal.archives-ouvertes.fr/hal-00670278

K. Avrachenkov, B. Ribeiro, and D. Towsley, Improving Random Walk Estimation Accuracy with Uniform Restarts, Algorithms and Models for the Web-Graph, pp.98-109, 2010.
DOI : 10.1007/978-3-642-18009-5_10
URL : https://hal.archives-ouvertes.fr/inria-00520350

F. Benevenuto, T. Rodrigues, M. Cha, and V. Almeida, Characterizing user behavior in online social networks, Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference, IMC '09, pp.49-62, 2009.
DOI : 10.1145/1644893.1644900

V. Bentkus and F. Gotze, The berry-esseen bound for student's statistic. The Annals of Probability, pp.491-503, 1996.

P. Brémaud, Markov chains: Gibbs fields, Monte Carlo simulation, and queue, 2013.
DOI : 10.1007/978-1-4757-3124-8

F. Chung and L. Lu, The average distances in random graphs with given expected degrees, Proceedings of the National Academy of Sciences, pp.15879-15882, 2002.

F. R. Chung, Spectral graph theory, 1997.
DOI : 10.1090/cbms/092

C. Cooper, T. Radzik, and Y. Siantos, Fast low-cost estimation of network properties using random walks, Algorithms and Models for the Web Graph, pp.130-143, 2013.
DOI : 10.1080/15427951.2016.1164100
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.639.9941

H. Cramér, Mathematical methods of statistics, 1999.

A. Gelman, Prior distributions for variance parameters in hierarchical models (comment on article by browne and draper), Bayesian analysis, vol.1, issue.3, pp.515-534, 2006.

M. Gjoka, M. Kurant, C. T. Butts, and A. Markopoulou, Practical Recommendations on Crawling Online Social Networks, IEEE Journal on Selected Areas in Communications, vol.29, issue.9, pp.1872-1892, 2011.
DOI : 10.1109/JSAC.2011.111011

M. Gjoka, M. Kurant, and A. , Markopoulou. 2.5 k-graphs: from sampling to generation, IEEE INFOCOM, pp.1968-1976, 2013.

S. Goel and M. J. Salganik, Respondent-driven sampling as Markov chain Monte Carlo, Statistics in Medicine, vol.7, issue.4, pp.2202-2229, 2009.
DOI : 10.2307/1390675
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3684629

A. Gut, Probability: A Graduate Course, 2013.
DOI : 10.1007/978-1-4614-4708-5

M. S. Handcock and K. J. Gile, Modeling social networks from sampled data, The Annals of Applied Statistics, vol.4, issue.1, pp.5-25, 2010.
DOI : 10.1214/08-AOAS221SUPP
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4637981

D. D. Heckathorn, Respondent-Driven Sampling: A New Approach to the Study of Hidden Populations, Social Problems, vol.44, issue.2, pp.174-199, 1997.
DOI : 10.2307/3096941

S. Jackman, Bayesian analysis for the social sciences, 2009.
DOI : 10.1002/9780470686621

J. G. Kemeny and J. L. Snell, Finite Markov Chains, 1983.

J. H. Koskinen, G. L. Robins, and P. E. Pattison, Analysing exponential random graph (p-star) models with missing data using Bayesian data augmentation, Statistical Methodology, vol.7, issue.3, pp.366-384, 2010.
DOI : 10.1016/j.stamet.2009.09.007

J. H. Koskinen, G. L. Robins, P. Wang, and P. E. Pattison, Bayesian analysis for partially observed network data, missing ties, attributes and actors, Social Networks, vol.35, issue.4, pp.514-527, 2013.
DOI : 10.1016/j.socnet.2013.07.003

J. Kunegis, KONECT, Proceedings of the 22nd International Conference on World Wide Web, WWW '13 Companion, pp.1343-1350, 2013.
DOI : 10.1145/2487788.2488173

C. Lee, X. Xu, and D. Y. Eun, Beyond random walk and metropolis-hastings samplers, ACM SIGMETRICS Performance Evaluation Review, vol.40, issue.1, pp.319-330, 2012.
DOI : 10.1145/2318857.2254795

J. Leskovec and A. Krevl, SNAP Datasets: Stanford large network dataset collection, 2014.

J. G. Ligo, G. K. Atia, and V. V. Veeravalli, A controlled sensing approach to graph classification, IEEE Transactions on Signal Processing, issue.24, pp.626468-6480, 2014.
DOI : 10.1109/icassp.2013.6638730

L. Massoulié, E. L. Merrer, A. Kermarrec, and A. Ganesh, Peer counting and sampling in overlay networks, Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing , PODC '06, pp.123-132, 2006.
DOI : 10.1145/1146381.1146402

R. Ottoni, J. P. Pesce, D. B. Las-casas, G. Franciscani-jr, W. M. Jr et al., Ladies first: Analyzing gender roles and behaviors in pinterest, ICWSM, 2013.

R. Pastor-satorras and A. Vespignani, Epidemic spreading in scale-free networks. Physical review letters, p.3200, 2001.

B. Ribeiro and D. Towsley, Estimating and sampling graphs with multidimensional random walks, Proceedings of the 10th annual conference on Internet measurement, IMC '10, 2010.
DOI : 10.1145/1879141.1879192
URL : http://arxiv.org/abs/1002.1751

B. Ribeiro, P. Wang, F. Murai, and D. Towsley, Sampling directed graphs with random walks, 2012 Proceedings IEEE INFOCOM, pp.1692-1700, 2012.
DOI : 10.1109/INFCOM.2012.6195540

S. K. Thompson, Targeted random walk designs, Survey Methodology, vol.32, issue.111, 2006.

H. C. Tijms, A first course in stochastic models, 2003.
DOI : 10.1002/047001363X

A. W. Van and . Vaart, Asymptotic statistics, 2000.