. Aalen, O. Odd, and S. Johansen, An empirical transition matrix for non-homogeneous Markov chains based on censored observations, Scandinavian Journal of Statistics, vol.118, pp.141-150, 1978.

L. Adamopoulos, Some counting and interval properties of the mutually-exciting processes, Journal of Applied Probability, vol.68, pp.78-86, 1975.

Y. Aït-sahalia, J. Cacho-diaz, and R. J. Laeven, Modeling financial contagion using mutually exciting jump processes, National Bureau of Economic Research, vol.69, p.211, 2010.

D. H. Alai and S. Arnold, Modelling cause-of-death mortality and the impact of cause-elimination, Annals of Actuarial Science, vol.95, issue.01, pp.167-186
DOI : 10.1093/biomet/71.1.75

D. Aldous, Stopping times and tightness. The Annals of Probability, pp.335-340, 1978.
DOI : 10.1214/aop/1176995579

URL : http://projecteuclid.org/download/pdf_1/euclid.aop/1176995579

P. Andersen, . Borgan, N. Gill, and . Keiding, Statistical Models Based on Counting Processes, pp.131-287, 1993.
DOI : 10.1007/978-1-4612-4348-9

S. Arnold and M. Sherris, Forecasting Mortality Trends Allowing for Cause-of-Death Mortality Dependence, North American Actuarial Journal, vol.8, issue.2, pp.273-282, 2013.
DOI : 10.1080/10920277.2013.838141

S. Arnold and M. Sherris, Causes-of-death mortality: What do we know on their dependence?, North American Actuarial Journal, vol.242, p.250, 2015.

S. Arnold, M. Sherris, and H. Lausanne, International cause-specific mortality rates: New insights from a cointegration analysis, p.242, 2015.

S. Arnold and A. Boumezoued, Cause-of-death mortality: What can be learned from population dynamics? HAL preprint Id: hal-01157900, p.34, 2015.

P. Auger, J. Poggiale, and E. Sánchez, A review on spatial aggregation methods involving several time scales, Ecological Complexity, vol.10, pp.12-25, 2012.
DOI : 10.1016/j.ecocom.2011.09.001

A. Baddeley, Spatial point processes and their applications Stochastic Geometry: Lectures given at the CIME Summer School, pp.1-75, 2004.

H. Bensusan, Risques de taux et de longévité: Modélisation dynamique et applications aux produits dérivés et à l'assurance vie, p.300, 2010.

H. Bensusan, A. Boumezoued, N. Karoui, and S. Loisel, Bridging the gap from microsimulation practice to population models: a survey. Work in progress, pp.300-307, 2010.

V. Bezborodov, Markov birth-and-death dynamics of populations. arXiv preprint, 2015.

E. Biffis, Affine processes for dynamic mortality and actuarial valuations, Insurance: Mathematics and Economics, vol.37, issue.3, pp.443-468, 2005.
DOI : 10.1016/j.insmatheco.2005.05.003

. Billiard, R. Sylvain, S. Ferrière, . Méléard, C. Viet et al., Stochastic dynamics of adaptive trait and neutral marker driven by eco-evolutionary feedbacks, Journal of Mathematical Biology, vol.34, issue.5, pp.1-32, 2014.
DOI : 10.1007/s00285-014-0847-y

URL : https://hal.archives-ouvertes.fr/hal-00875991

P. Billingsley, Convergence of probability measures, pp.311-313, 2009.
DOI : 10.1002/9780470316962

D. Blanchet, S. Buffeteau, E. Crenner, and S. L. Minez, The destinie 2 microsimulation model: overview and illustrative results. 2 nd IMA conference, pp.158-168, 2009.

D. E. Bloom and D. Canning, Commentary: The Preston Curve 30 years on: still sparking fires, International Journal of Epidemiology, vol.36, issue.3, pp.498-499, 2007.
DOI : 10.1093/ije/dym079

B. Bolker, W. Stephen, and . Pacala, Using Moment Equations to Understand Stochastically Driven Spatial Pattern Formation in Ecological Systems, Theoretical Population Biology, vol.52, issue.3, pp.179-197, 1997.
DOI : 10.1006/tpbi.1997.1331

C. Bonnet, C. Burricand, C. Colin, A. Flipo, P. R. Mahieu et al., Le modèle de microsimulation dynamique: Destinie, p.240, 1999.

A. Boumezoued, Macroscopic behavior of heterogenous populations with fast random life histories, Working Paper, vol.6, issue.35, p.268, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01245249

A. Boumezoued, Population viewpoint on Hawkes processes. HAL preprint Id: hal-01149752, To appear in Advances in Applied Probability 48, p.175, 2015.
DOI : 10.1017/apr.2016.10

URL : https://hal.archives-ouvertes.fr/hal-01149752

A. Boumezoued, N. Karoui, and S. Loisel, Measuring mortality heterogeneity dynamics with interval-censored data. Working Paper, p.299, 2015.

A. Bovier and S. Wang, Trait substitution trees on two time scales analysis. arXiv preprint, p.300, 2013.

P. Brémaud and L. Massoulié, Stability of nonlinear Hawkes processes. The Annals of Probability, pp.1563-1588, 1996.

P. Brémaud and L. Massoulié, Power spectra of general shot noises and Hawkes point processes with a random excitation Advances in Applied Probability 205?222, pp.75-210, 2002.

A. S. Bryk, W. Stephen, and . Raudenbush, Hierarchical linear models: applications and data analysis methods, p.162, 1992.

A. J. Cairns, D. Blake, K. Dowd, and A. Kessler, Phantoms never die: Living with unreliable mortality data, pp.163-244, 2014.
DOI : 10.2139/ssrn.2676648

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.697.7736

A. J. Cairns, D. Blake, and K. Dowd, A Two-Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration, Journal of Risk & Insurance, vol.10, issue.4, pp.687-718, 2006.
DOI : 10.2143/AST.33.1.1039

. Cairns, J. Andrew, D. Blake, and K. Dowd, Modelling and management of mortality risk: a review, Scandinavian Actuarial Journal, vol.11, issue.2-3, pp.79-113, 2008.
DOI : 10.1017/S1357321700002762

. Cairns, J. Andrew, D. Blake, K. Dowd, D. Guy et al., A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States, North American Actuarial Journal, vol.8, issue.1, pp.1-35, 2009.
DOI : 10.1080/10920277.2009.10597538

D. Canning, The causes and consequences of demographic transition, Population Studies, vol.120, issue.3, pp.353-361, 2011.
DOI : 10.2307/146149

J. F. Carriere, Dependent decrement theory, Transactions of the Society of Actuaries, vol.46, issue.238, pp.45-74, 1994.

N. Champagnat, R. Ferrière, and S. Méléard, Unifying evolutionary dynamics: From individual stochastic processes to macroscopic models, Theoretical Population Biology, vol.69, issue.3, pp.297-321, 0197.
DOI : 10.1016/j.tpb.2005.10.004

URL : https://hal.archives-ouvertes.fr/inria-00164784

C. L. Chiang, Introduction to stochastic processes in biostatistics, p.242, 1968.

S. Clémençon, V. C. Tran, and H. De-arazoza, A stochastic SIR model with contact-tracing: large population limits and statistical inference, Journal of Biological Dynamics, vol.17, issue.4, pp.392-414, 2008.
DOI : 10.2307/1427670

J. E. Cohen, Human Population: The Next Half Century, Science, vol.302, issue.5648, pp.1172-1175, 2003.
DOI : 10.1126/science.1088665

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.453.3842

D. Commenges and A. Gégout-petit, Likelihood for Generally Coarsened Observations from Multistate or Counting Process Models, Scandinavian Journal of Statistics, vol.38, issue.2, pp.432-450, 2007.
DOI : 10.1006/jmva.1998.1807

URL : https://hal.archives-ouvertes.fr/hal-00294300

D. Commenges, P. Joly, A. Gégout-petit, and B. Liquet, Choice between Semi-parametric Estimators of Markov and Non-Markov Multi-state Models from Coarsened Observations, Scandinavian Journal of Statistics, vol.11, issue.1, pp.33-52, 2007.
DOI : 10.1214/aos/1013203457

URL : https://hal.archives-ouvertes.fr/hal-00194275

M. Costa, A piecewise deterministic model for prey-predator communities. arXiv preprint, p.300, 2015.
DOI : 10.1214/16-aap1182

URL : http://arxiv.org/abs/1503.02492

M. Costa, C. Hauzy, N. Loeuille, and S. Méléard, Stochastic ecoevolutionary model of a prey-predator community, Journal of mathematical biology, vol.144, pp.1-50, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01023709

D. Cutler and G. Miller, The Role of Public Health Improvements in Health Advances: The Twentieth-Century United States, Demography, vol.42, issue.1, pp.1-22, 2005.
DOI : 10.1353/dem.2005.0002

D. M. Cutler, S. Angus, A. Deaton, and . Lleras-muney, The determinants of mortality, National Bureau of Economic Research, p.160, 2006.

C. Czado and F. Rudolph, Application of survival analysis methods to long-term care insurance, Insurance: Mathematics and Economics, vol.31, issue.3, pp.395-413, 2002.
DOI : 10.1016/S0167-6687(02)00186-5

D. Fonseca, J. , and R. Zaatour, Hawkes Process: Fast Calibration, Application to Trade Clustering and Diffusive Limit, SSRN Electronic Journal, vol.34, issue.69, pp.548-579, 2014.
DOI : 10.2139/ssrn.2294112

D. Daley, D. Vere, and -. , An Introduction to the Theory of Point Processes. Volume I: Elementary Theory and Methods of Probability and its Applications, p.224, 2003.

D. Daley, D. Vere, and -. , An introduction to the theory of point processes. Volume II: General theory and structure. probability and its applications, p.222, 2008.

A. Dassios and H. Zhao, A dynamic contagion process Advances in applied probability, pp.814-846, 2011.

A. Dassios and H. Zhao, Exact simulation of Hawkes process with exponentially decaying intensity, Electronic Communications in Probability, vol.18, issue.0, 2013.
DOI : 10.1214/ECP.v18-2717

S. Delattre, N. Fournier, and M. Hoffmann, High dimensional Hawkes processes, p.223, 2014.

A. Delwarde and M. Denuit, Construction de tables de mortalité périodiques et prospectives, Economica, vol.18, p.250, 2006.

B. Diaz, T. Aparicio, A. Fent, L. Prskawetz, and . Bernardi, Projections of age-specific fertility rates through an agent-based model of social interaction. Work session on demographic projections 49, p.165, 2007.

U. Dieckmann, R. Law-dieckmann, R. Law, and . Metz, Relaxation projections and the method of moments. The Geometry of Ecological Interactions: Simplifying Spatial Complexity, pp.412-455, 2000.

D. S. Dimitrova, S. Haberman, and V. K. Kaishev, Dependent competing risks: Cause elimination and its impact on survival, Insurance: Mathematics and Economics, vol.53, issue.2, pp.238-243, 2013.
DOI : 10.1016/j.insmatheco.2013.07.008

URL : http://openaccess.city.ac.uk/12437/1/Dimitrova%20et%20al%20%20%282013%29%20IME.pdf

P. Donnelly, Explaining the Glasgow effect: could adverse childhood experiences play a role?, Public Health, vol.124, issue.9, pp.498-499, 2010.
DOI : 10.1016/j.puhe.2010.05.013

M. Doumic, M. Hoffmann, N. Krell, and L. Robert, Statistical estimation of a growth-fragmentation model observed on a genealogical tree, Bernoulli, vol.21, issue.3, pp.1760-1799, 2015.
DOI : 10.3150/14-BEJ623

URL : https://hal.archives-ouvertes.fr/hal-01102799

M. Doumic, M. Hoffmann, P. Reynaud-bouret, and V. Rivoirard, Nonparametric Estimation of the Division Rate of a Size-Structured Population, SIAM Journal on Numerical Analysis, vol.50, issue.2, pp.925-950, 2012.
DOI : 10.1137/110828344

URL : https://hal.archives-ouvertes.fr/hal-00578694

M. Duée, La modélisation des comportements démographiques dans le modèle de microsimulation Destinie, p.240, 2005.

R. C. Elandt-johnson, Conditional failure time distributions under competing risk theory with dependent failure times and proportional hazard rates, Scandinavian Actuarial Journal, vol.27, issue.1, pp.37-51, 1976.
DOI : 10.2307/2528828

S. Engen, A. Bakke, and . Islam, Demographic and Environmental Stochasticity-Concepts and Definitions, Biometrics, vol.54, issue.3, pp.840-846, 1998.
DOI : 10.2307/2533838

E. Errais, K. Giesecke, and L. Goldberg, Affine Point Processes and Portfolio Credit Risk, SIAM Journal on Financial Mathematics, vol.1, issue.1, pp.642-665, 2010.
DOI : 10.1137/090771272

R. Ferriere and V. C. Tran, Stochastic and deterministic models for age-structured populations with genetically variable traits, ESAIM: Proceedings, pp.289-310, 2009.
DOI : 10.1051/proc/2009033

URL : https://hal.archives-ouvertes.fr/hal-00323683

R. W. Fogel, Chapter 9 New findings on secular trends in nutrition and mortality: Some implications for population theory, p.160, 1997.
DOI : 10.1016/S1574-003X(97)80026-8

Y. Foucher, M. Giral, J. Soulillou, and J. Daures, A semi-Markov model for multistate and interval-censored data with multiple terminal events. Application in renal transplantation, Statistics in Medicine, vol.16, issue.30, pp.5381-5393, 2007.
DOI : 10.1002/sim.3100

M. Fougère and M. Mérette, Population ageing and economic growth in seven OECD countries, Economic Modelling, vol.16, issue.3, pp.411-427, 1999.
DOI : 10.1016/S0264-9993(99)00008-5

N. Fournier and S. Méléard, A microscopic probabilistic description of a locally regulated population and macroscopic approximations, The Annals of Applied Probability, vol.14, issue.4, pp.1880-1919, 2004.
DOI : 10.1214/105051604000000882

J. F. Fries, Aging, Natural Death, and the Compression of Morbidity, New England Journal of Medicine, vol.303, issue.3, pp.130-135, 1980.
DOI : 10.1056/NEJM198007173030304

H. Frydman, Nonparametric estimation of a Markov 'illness-death' process from interval-censored observations, with application to diabetes survival data, Biometrika, vol.82, issue.120, pp.773-789, 1995.

H. Frydman and M. Szarek, Nonparametric Estimation in a Markov ???Illness-Death??? Process from Interval Censored Observations with Missing Intermediate Transition Status, Biometrics, vol.38, issue.1, pp.143-151, 2009.
DOI : 10.1111/j.1541-0420.2008.01056.x

N. L. Garcia, G. Thomas, and . Kurtz, Spatial birth and death processes as solutions of stochastic equations, Alea, vol.1, issue.224, pp.281-303, 2006.

N. L. Garcia, G. Thomas, and . Kurtz, Spatial Point Processes and the Projection Method, and Out of Equilibrium 2, pp.271-298, 2008.
DOI : 10.1007/978-3-7643-8786-0_13

N. Garcia and . Lopes, Birth and death processes as projections of higher-dimensional Poisson processes Advances in applied probability 911?930, p.179, 1995.

F. Gaüzère, D. Commenges, P. Barberger-gateau, and L. Letenneur, Jean- François Dartigues Maladie et dépendance: description des évolutions par des modèles multi-états, Population, vol.119, pp.205-222, 1999.

L. Gavrilov and . Gavrilova, The biology of life span: A quantitative approach, Free Radical Biology and Medicine, vol.12, issue.4, p.285, 1991.
DOI : 10.1016/0891-5849(92)90121-V

F. Girosi and G. King, Demographic forecasting, p.242, 2006.

B. Gompertz, On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies, Philosophical transactions of the Royal Society of London, vol.123, issue.163, pp.513-583, 1825.

L. Gray, H. Alastair, and . Leyland, A multilevel analysis of diet and socio-economic status in Scotland: investigating the ???Glasgow effect???, Public Health Nutrition, vol.8, issue.09, pp.1351-1358, 2009.
DOI : 10.1038/sj.ijo.0800405

B. Grigelionis, The representation of integer-valued random measures as stochastic integrals over the Poisson measure, Litovsk. Mat. Sb, vol.11, issue.178, pp.93-108, 1971.

C. Z. Guilmoto, Skewed sex ratios at birth and future marriage squeeze in China and India, Demography, vol.49, issue.205, pp.2005-2100, 2012.

A. Gupta, . Metz, C. Viet, and . Tran, A New Proof for the Convergence of an Individual Based Model to the Trait Substitution Sequence, Acta Applicandae Mathematicae, vol.52, issue.1, pp.1-27, 2014.
DOI : 10.1007/s10440-013-9847-y

URL : https://hal.archives-ouvertes.fr/hal-00678007

S. Hardiman, N. Bercot, and J. Bouchaud, Critical reflexivity in financial markets: a Hawkes process analysis. arXiv preprint, 2013.

T. E. Harris, The theory of branching processes, 1963.
DOI : 10.1007/978-3-642-51866-9

S. Hautphenne and G. Latouche, The Markovian binary tree applied to demography, Journal of Mathematical Biology, vol.21, issue.2, pp.1109-1135, 2012.
DOI : 10.1007/s00285-011-0437-1

A. G. Hawkes, Spectra of some self-exciting and mutually exciting point processes, Biometrika, vol.58, issue.1, pp.83-90, 1971.
DOI : 10.1093/biomet/58.1.83

A. G. Hawkes and D. Oakes, A cluster process representation of a self-exciting process, Journal of Applied Probability, vol.493503, issue.213, pp.210-211, 1974.

F. Helms, C. Czado, and S. Gschlößl, Calculation of LTC Premiums Based on Direct Estimates of Transition Probabilities, ASTIN Bulletin, vol.5, issue.02, pp.455-469, 2005.
DOI : 10.1080/01621459.1995.10476572

H. Hock, N. David, and . Weil, On the dynamics of the age structure, dependency, and consumption, Journal of Population Economics, vol.58, issue.2, pp.1019-1043, 2012.
DOI : 10.1007/s00148-011-0372-x

M. Hoffmann and A. Olivier, Nonparametric estimation of the division rate of an age dependent branching process, Stochastic Processes and their Applications, vol.126, issue.5, 2014.
DOI : 10.1016/j.spa.2015.11.009

URL : https://hal.archives-ouvertes.fr/hal-01102813

R. J. Hyndman and H. Booth, Stochastic population forecasts using functional data models for mortality, fertility and migration, International Journal of Forecasting, vol.24, issue.3, pp.323-342, 2008.
DOI : 10.1016/j.ijforecast.2008.02.009

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.9339

M. Iannelli, M. Martcheva, and F. A. Milner, Gender-structured population modeling: mathematical methods, numerics, and simulations, pp.244-264, 2005.
DOI : 10.1137/1.9780898717488

C. H. Jackson, Multi-state models for panel data: the msm package for r, Journal of Statistical Software, vol.38, issue.8, pp.1-29, 2011.

J. Jacod, Calcul stochastique et problemes de martingales, p.43, 1979.
DOI : 10.1007/BFb0064907

J. Jensen, J. Ledet, and . Møller, Pseudolikelihood for exponential family models of spatial point processes. The Annals of Applied Probability, pp.445-461, 1991.

A. Joffe and M. Métivier, Weak convergence of sequences of semimartingales with applications to multitype branching processes, Advances in Applied Probability, pp.20-65, 1986.

P. Joly, D. Commenges, C. Helmer, and L. Letenneur, A penalized likelihood approach for an illness-death model with interval-censored data: application to age-specific incidence of dementia, Biostatistics, vol.3, issue.3, pp.433-443, 2002.
DOI : 10.1093/biostatistics/3.3.433

URL : https://hal.archives-ouvertes.fr/inserm-00182448

B. Jourdain, S. Méléard, A. Wojbor, and . Woyczynski, L??vy flights in evolutionary ecology, Journal of Mathematical Biology, vol.26, issue.2, pp.677-707, 2012.
DOI : 10.1007/s00285-011-0478-5

S. Jovanovi?, J. Hertz, and S. Rotter, Cumulants of Hawkes point processes. arXiv preprint arXiv:1409.5353, p.211, 2014.

V. K. Kaishev, D. S. Dimitrova, and S. Haberman, Modelling the joint distribution of competing risks survival times using copula functions, Insurance: Mathematics and Economics, vol.41, issue.3, p.242, 2007.
DOI : 10.1016/j.insmatheco.2006.11.006

J. Kalbfleisch, F. Jerald, and . Lawless, The Analysis of Panel Data under a Markov Assumption, Journal of the American Statistical Association, vol.75, issue.392, pp.863-871, 1985.
DOI : 10.1080/01621459.1985.10478195

M. Kang, W. Stephen, and . Lagakos, Statistical methods for panel data from a semi-Markov process, with application to HPV, Biostatistics, vol.8, issue.2, pp.252-264, 2007.
DOI : 10.1093/biostatistics/kxl006

N. Keiding, Statistical Inference in the Lexis Diagram, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol.332, issue.1627, pp.487-509, 1627.
DOI : 10.1098/rsta.1990.0128

D. G. Kendall, Stochastic processes and population growth, Journal of the Royal Statistical Society. Series B (Methodological), vol.11, issue.52, pp.230-282, 1949.

N. Keyfitz, Changing vital rates and age distributions, Population Studies, vol.22, issue.2, pp.235-251, 1968.
DOI : 10.2307/3348332

N. Keyfitz, The mathematics of sex and marriage, Proceedings of the sixth Berkeley symposium on mathematical statistics and probability, pp.89-108, 1972.

C. Kuehn, Moment closure-a brief review. arXiv preprint, p.197, 2015.
DOI : 10.1007/978-3-319-28028-8_13

URL : http://arxiv.org/abs/1505.02190

T. Kurtz, Stochastic processes as projections of Poisson random measures. special invited paper at ims meeting, p.179, 1989.

T. G. Kurtz, Averaging for martingale problems and stochastic approximation Applied Stochastic Analysis, pp.186-209, 1992.
DOI : 10.1007/bfb0007058

. Kwon, . Hyuk-sung, L. Bruce, and . Jones, The impact of the determinants of mortality on life insurance and annuities, Insurance: Mathematics and Economics, vol.38, issue.2, pp.271-288, 2006.
DOI : 10.1016/j.insmatheco.2005.08.007

. Kwon, . Hyuk-sung, L. Bruce, and . Jones, Applications of a multi-state risk factor/mortality model in life insurance, Insurance: Mathematics and Economics, vol.43, issue.3, pp.394-402, 2008.
DOI : 10.1016/j.insmatheco.2008.07.004

R. D. Lee and L. R. Carter, Modeling and forecasting US mortality, Journal of the American Statistical Association, vol.87, issue.419, pp.659-671, 1992.

S. Levantesi and M. Menzietti, Managing longevity and disability risks in life annuities with long term care, Insurance: Mathematics and Economics, vol.50, issue.3, pp.391-401, 2012.
DOI : 10.1016/j.insmatheco.2012.01.004

P. A. Lewis and . Shedler, Simulation of nonhomogeneous poisson processes by thinning, Naval Research Logistics Quarterly, vol.32, issue.3, p.222, 1978.
DOI : 10.1002/nav.3800260304

J. Li and C. O. Donoghue, A survey of dynamic microsimulation models: uses, model structure and methodology, International Journal of Microsimulation, vol.6, issue.2, pp.3-55, 2013.

K. G. Manton, Past and Future Life Expectancy Increases At Later Ages: Their Implications for the Linkage of Chronic Morbidity, Disability, and Mortality, Journal of Gerontology, vol.41, issue.5, pp.672-681, 1986.
DOI : 10.1093/geronj/41.5.672

K. G. Manton, E. Stallard, and J. W. Vaupel, Alternative Models for the Heterogeneity of Mortality Risks among the Aged, Journal of the American Statistical Association, vol.27, issue.395, pp.81-635, 1986.
DOI : 10.1080/01621459.1986.10478316

L. Massoulié, Stability results for a general class of interacting point processes dynamics, and applications, Stochastic processes and their applications, pp.1-30, 1998.

L. Mayhew and D. Smith, A new method of projecting populations based on trends in life expectancy and survival, Population Studies, vol.29, issue.3, pp.157-170, 2013.
DOI : 10.1038/nature08984

B. Mckendrick and A. G. , Applications of Mathematics to Medical Problems, Proc. Edin. Math. Soc. 54 98?130, pp.143-239, 1926.
DOI : 10.1038/104660a0

T. Mckeown, The modem rise of population, p.160, 1976.

S. Méléard and S. Roelly, Sur les convergences étroite ou vague de processus à valeurs mesures. Comptes rendus de l'Académie des sciences, Mathématique, vol.1, issue.3178, pp.785-788, 1993.

S. Méléard and C. Tran, Slow and fast scales for superprocess limits of age-structured populations, Stochastic Processes and their Applications, vol.122, issue.1, pp.250-276, 2012.
DOI : 10.1016/j.spa.2011.08.007

J. A. Metz, A. Stefan, G. Geritz, . Meszéna, J. Frans et al., Adaptive dynamics, a geometrical study of the consequences of nearly faithful reproduction. Stochastic and spatial structures of dynamical systems 45, pp.183-231, 0197.

B. Mirkin and M. B. Weinberger, The demography of population ageing, Population Bulletin of the United Nations, vol.42, issue.43, pp.37-53, 2001.

D. Oakes, The markovian self-exciting process, Journal of Applied Probability, vol.26, issue.211, pp.69-77, 1975.
DOI : 10.1017/s0021900200033106

K. Oelschlager, Limit theorems for age-structured populations. The Annals of Probability 290?318, p.248, 1990.
DOI : 10.1214/aop/1176990950

Y. Ogata, On Lewis' simulation method for point processes. Information Theory, IEEE Transactions on, vol.27, issue.178, pp.23-31, 1981.
DOI : 10.1109/tit.1981.1056305

G. H. Orcutt, A New Type of Socio-Economic System, The Review of Economics and Statistics, vol.39, issue.2, pp.116-123, 1957.
DOI : 10.2307/1928528

M. J. Plank and R. Law, Spatial Point Processes and Moment Dynamics in the Life Sciences: A Parsimonious Derivation and Some Extensions, Bulletin of Mathematical Biology, vol.270, issue.2, pp.586-613, 0197.
DOI : 10.1007/s11538-014-0018-8

R. Plat, On stochastic mortality modeling, Insurance: Mathematics and Economics, vol.45, issue.3, pp.393-404, 2009.
DOI : 10.1016/j.insmatheco.2009.08.006

R. L. Prentice, J. D. Kalbfleisch, A. V. Peterson-jr, N. Flournoy, V. Farewell et al., The Analysis of Failure Times in the Presence of Competing Risks, Biometrics, vol.34, issue.4, pp.541-554, 1978.
DOI : 10.2307/2530374

S. H. Preston, The Changing Relation between Mortality and level of Economic Development, Population Studies, vol.46, issue.2, pp.231-248, 1975.
DOI : 10.2307/2172340

H. Putter, R. Fiocco, and . Geskus, Tutorial in biostatistics: competing risks and multi-state models, Statistics in Medicine, vol.6, issue.11, pp.2389-2430, 2007.
DOI : 10.1002/sim.2712

M. Rambaldi, P. Pennesi, and F. Lillo, Modeling FX market activity around macroeconomic news: a Hawkes process approach. arXiv preprint, pp.75-225, 2014.
DOI : 10.1103/physreve.91.012819

S. Richards, Applying Survival Models to Pensioner Mortality Data, British Actuarial Journal, vol.2, issue.02, pp.257-303, 2008.
DOI : 10.2307/2683925

S. Roelly-coppoletta, A criterion of convergence of measure???valued processes: application to measure branching processes, Stochastics, vol.8, issue.1-2, pp.43-65, 1986.
DOI : 10.1007/BF00736006

C. Rooney, C. Griffiths, and L. Cook, The implementation of ICD-10 for cause of death coding-some preliminary results from the bridge coding study, Health Statistics Quarterly, issue.13, pp.31-41, 2002.

M. Rosen, Forecasting life expectancy and mortality in sweden, some comments on methodological problems and potential approaches, technical report 4. Tech. rep., Social Insurance Studies from the Swedish Social Insurance, p.242, 2006.

A. Saichev and D. Sornette, Generating functions and stability study of multivariate self-excited epidemic processes, The European Physical Journal B, vol.77, issue.2, pp.271-282, 2011.
DOI : 10.1140/epjb/e2011-20298-3

R. Schoen, Measuring the Tightness of a Marriage Squeeze, Demography, vol.20, issue.1, pp.61-78, 1983.
DOI : 10.2307/2060901

E. Silverman, J. Bijak, and J. Noble, Feeding the beast: can computational demographic models free us from the tyranny of data, p.163, 2011.

M. Spielauer, What is Social Science Microsimulation?, Social Science Computer Review, vol.29, issue.1, pp.9-20, 2011.
DOI : 10.1177/0894439310370085

B. L. Strehler, S. Albert, and . Mildvan, General Theory of Mortality and Aging, Science, vol.132, issue.3418, pp.14-21, 1960.
DOI : 10.1126/science.132.3418.14

H. Strulik and S. Vollmer, Long-run trends of human aging and longevity, Journal of Population Economics, vol.48, issue.4, pp.1303-1323, 2013.
DOI : 10.1007/s00148-012-0459-z

S. Subramanian, K. Jones, and C. Duncan, Multilevel methods for public health research. Neighborhoods and health, p.162, 2003.
DOI : 10.1093/acprof:oso/9780195138382.003.0004

L. Tesfatsion, Agent-Based Computational Economics: Growing Economies From the Bottom Up, Artificial Life, vol.84, issue.1, pp.55-82, 2002.
DOI : 10.1023/A:1013814511151

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.194.4605

A. C. Titman, D. Linda, and . Sharples, Semi-Markov Models with Phase-Type Sojourn Distributions, Biometrics, vol.27, issue.3, pp.742-752, 2010.
DOI : 10.1111/j.1541-0420.2009.01339.x

C. Touraine, Modèles illness-death pour données censurées par intervalle: application à l'étude de la démence, p.270, 2013.

C. Touraine, C. Helmer, and P. Joly, Predictions in an illness-death model. Statistical methods in medical research 0962280213489234, p.279, 2013.
DOI : 10.1177/0962280213489234

V. C. Tran, Modèles particulaires stochastiques pour des problèmes d'évolution adaptative et pour l'approximation de solutions statistiques, p.309, 2006.

V. C. Tran, Large population limit and time behaviour of a stochastic particle model describing an age-structured population, ESAIM: Probability and Statistics, vol.12, issue.301, pp.345-386, 2008.
DOI : 10.1051/ps:2007052

URL : https://hal.archives-ouvertes.fr/hal-00122191

S. P. Tsai, E. S. Lee, and R. J. Hardy, The effect of a reduction in leading causes of death: potential gains in life expectancy., American Journal of Public Health, vol.68, issue.10, p.242, 1978.
DOI : 10.2105/AJPH.68.10.966

A. Tsiatis, A non-identifiability aspect of the problem of competing risks, Proceedings of the National Academy of Sciences, p.242, 1975.

. Van-imhoff, W. Evert, and . Post, Microsimulation methods for population projection, Population, vol.10, issue.168, pp.97-136, 1998.

J. W. Vaupel and A. I. Yashin, The deviant dynamics of death in heterogeneous populations . technical report rr-83-001, Tech. rep., International Institute for Applied Systems Analysis (IIASA), p.242, 1983.

C. T. Volinsky, E. Adrian, and . Raftery, Bayesian Information Criterion for Censored Survival Models, Biometrics, vol.46, issue.1, pp.256-262, 2000.
DOI : 10.1111/j.0006-341X.2000.00256.x

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.142.9660

V. Foerster and H. , The Kinetics of Cellular Proliferation. Grune & Stratton, pp.239-300, 1959.

V. Neumann and J. , Various techniques used in connection with random digits, p.47, 1951.

. Wang and J. Frank, A central limit theorem for age- and density-dependent population processes, Stochastic Processes and their Applications, pp.173-193, 1977.
DOI : 10.1016/0304-4149(77)90028-X

URL : http://doi.org/10.1016/0304-4149(77)90028-x

S. Wei, Multi-state models for interval censored data with competing risk, p.270, 2015.

S. Wheatley, V. Filimonov, and D. Sornette, Estimation of the Hawkes process with renewal immigration using the EM algorithm. Swiss Finance Institute Research Paper, pp.14-53, 2014.

F. Willekens, Biographic forecasting: bridging the micro-macro gap in population forecasting, New Zealand population review, vol.31, issue.158, pp.77-124, 2005.

R. Willets, The Cohort Effect: Insights and Explanations, British Actuarial Journal, vol.309, issue.04, pp.164-189, 2004.
DOI : 10.1136/thx.45.9.657

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.665.6304

J. R. Wilmoth, Are mortality projections always more pessimistic when disaggregated by cause of death? Mathematical Population Studies, p.242, 1995.

J. R. Wilmoth and S. Horiuchi, Rectangularization Revisited: Variability of Age at Death within Human Populations, Demography, vol.36, issue.4, pp.475-495, 1999.
DOI : 10.2307/2648085

S. M. Zemyan, The Classical Theory of Integral Equations, p.319, 2012.
DOI : 10.1007/978-0-8176-8349-8