pomp:
statistical inference for
partially-observed Markov processes

Bibliography

 
P. P. Martinez, R. C. Reiner Jr, M. Roy, B. A. Cash, M. Yunus, A. S. G. Faruque, S. Huq, A. A. King, and M. Pascual (2017) Cholera forecast for Dhaka, Bangladesh, with the 2015–2016 El Niño: Lessons learned. PLoS ONE, 12: e0172355. Link
 
M. G. Buhnerkempe, K. C. Prager, C. C. Strelioff, D. J. Greig, J. L. Laake, S. R. Melin, R. L. DeLong, F. M. D. Gulland, and J. O. Lloyd-Smith (2017) Detecting signals of chronic shedding to explain pathogen persistence: Leptospira interrogans in California sea lions. Journal of Animal Ecology, Link
 
S. Tavakoli and V. M. Panaretos (2016) Detecting and localizing differences in functional time series dynamics: a case study in molecular biophysics. Journal of the American Statistical Association, 111: 1020–1035. Link
 
P. P. Martinez, A. A. King, M. Yunus, A. S. G. Faruque, and M. Pascual (2016) Differential and enhanced response to climate forcing in diarrheal disease due to rotavirus across a megacity of the developing world. Proceedings of the National Academy of Sciences of the U.S.A., 113: 4092–4097. Link
 
F. M. G. Magpantay, M. Domenech de Cellès, P. Rohani, and A. A. King (2016) Pertussis immunity and epidemiology: mode and duration of vaccine-induced immunity. Parasitology, 143: 835–849. Link
 
A. A. King, D. Nguyen, and E. L. Ionides (2016) Statistical inference for partially observed Markov processes via the R package pomp. Journal of Statistical Software, 69: 1–43. Link
 
M. Fasiolo, N. Pya, and S. N. Wood (2016) A comparison of inferential methods for highly nonlinear state space models in ecology and epidemiology. Statistical Science, 31: 96–118. Link
 
A. D. Becker, R. B. Birger, A. Teillant, P. A. Gastanaduy, G. S. Wallace, and B. T. Grenfell (2016) Estimating enhanced prevaccination measles transmission hotspots in the context of cross-scale dynamics. Proceedings of the National Academy of Sciences of the U.S.A., 113: 14595–14600. Link
 
D. Barrows (2016) A Comparative Study of Techniques for Estimation and Inference of Nonlinear Stochastic Time Series. Thesis: McMaster University. Link
 
K. M. Bakker, M. E. Martinez-Bakker, B. Helm, and T. J. Stevenson (2016) Digital epidemiology reveals global childhood disease seasonality and the effects of immunization. Proceedings of the National Academy of Sciences of the U.S.A., 113: 6689–6694. Link
 
S. Shrestha, B. Foxman, J. Berus, W. G. van Panhuis, C. Steiner, C. Viboud, and P. Rohani (2015) The role of influenza in the epidemiology of pneumonia. Scientific Reports, 5: 15314–. Link
 
E. O. Romero-Severson, E. Volz, J. S. Koopman, T. Leitner, and E. L. Ionides (2015) Dynamic variation in sexual contact rates in a cohort of HIV-negative gay men. American Journal of Epidemiology, 182: 255–262. Link
 
M. Martinez-Bakker, A. A. King, and P. Rohani (2015) Unraveling the transmission ecology of polio. PLoS Biology, 13: e1002172. Link
 
K. Laneri, R. E. Paul, A. Tall, J. Faye, F. Diene-Sarr, C. Sokhna, J.-F. Trape, and X. Rodó (2015) Dynamical malaria models reveal how immunity buffers effect of climate variability. Proceedings of the National Academy of Sciences of the U.S.A., 112: 8786–8791. Link
 
A. A. King, M. Domenech de Cellès, F. M. G. Magpantay, and P. Rohani (2015) Avoidable errors in the modelling of outbreaks of emerging pathogens, with special reference to Ebola. Proceedings of the Royal Society of London, Series B, 282: 20150347. Link
 
E. L. Ionides, D. Nguyen, Y. Atchadé, S. Stoev, and A. A. King (2015) Inference for dynamic and latent variable models via iterated, perturbed Bayes maps. Proceedings of the National Academy of Sciences of the U.S.A., 112: 719–724. Link
 
D. T. S. Hayman (2015) Biannual birth pulses allow filoviruses to persist in bat populations. Proceedings of the Royal Society of London, Series B, 282: 20142591. Link
 
C. Bretó (2014) On idiosyncratic stochasticity of financial leverage effects. Statistics and Probability Letters, 91: 20–26. Link
 
I. M. Blake, R. Martin, A. Goel, N. Khetsuriani, J. Everts, C. Wolff, S. Wassilak, R. B. Aylward, and N. C. Grassly (2014) The role of older children and adults in wild poliovirus transmission. Proceedings of the National Academy of Sciences of the U.S.A., 111: 10604–10609. Link
 
S. Shrestha, B. Foxman, D. M. Weinberger, C. Steiner, C. Viboud, and P. Rohani (2013) Identifying the interaction between influenza and pneumococcal pneumonia using incidence data. Science Translational Medicine, 5: 191ra84. Link
 
J. S. Lavine, A. A. King, V. Andreasen, and O. N. Bjørnstad (2013) Immune boosting explains regime-shifts in prevaccine-era pertussis dynamics. PLoS ONE, 8: e72086. Link
 
D. He, J. Dushoff, R. Eftimie, and D. J. D. Earn (2013) Patterns of spread of influenza A in Canada. Proceedings of the Royal Society of London, Series B, 280: 20131174. Link
 
D. He, J. Dushoff, T. Day, J. Ma, and D. J. D. Earn (2013) Inferring the causes of the three waves of the 1918 influenza pandemic in England and Wales. Proceedings of the Royal Society of London, Series B, 280: 20131345. Link
 
J. C. Blackwood, D. G. Streicker, S. Altizer, and P. Rohani (2013) Resolving the roles of immunity, pathogenesis, and immigration for rabies persistence in vampire bats. Proceedings of the National Academy of Sciences of the U.S.A., 110: 20837–20842. Link
 
J. C. Blackwood, D. A. T. Cummings, H. Broutin, S. Iamsirithaworn, and P. Rohani (2013) Deciphering the impacts of vaccination and immunity on pertussis epidemiology in Thailand. Proceedings of the National Academy of Sciences of the U.S.A., 110: 9595–9600. Link
 
J.-M. Marin, P. Pudlo, C. P. Robert, and R. J. Ryder (2012) Approximate Bayesian computational methods. Statistics and Computing, 22: 1167–1180. Link
 
Y. Xia and H. Tong (2011) Feature matching in time series modeling. Statistical Science, 26: 21–46. Link
 
S. Shrestha, A. A. King, and P. Rohani (2011) Statistical inference for multi-pathogen systems. PLoS Computational Biology, 7: e1002135. Link
 
J. Knape and P. de Valpine (2011) Fitting complex population models by combining particle filters with Markov chain Monte Carlo. Ecology, 93: 256–263. Link
 
E. L. Ionides, A. Bhadra, Y. Atchadé, and A. A. King (2011) Iterated filtering. Annals of Statistics, 39: 1776–1802. Link
 
E. L. Ionides (2011) Discussion of “Feature Matching in Time Series Modeling” by Y. Xia and H. Tong. Statistical Science, 26: 49–52. Link
 
D. He, J. Dushoff, T. Day, J. Ma, and D. Earn (2011) Mechanistic modelling of the three waves of the 1918 influenza pandemic. Theoretical Ecology, 4: 1–6. Link
 
A. Camacho, S. Ballesteros, A. L. Graham, F. Carrat, O. Ratmann, and B. Cazelles (2011) Explaining rapid reinfections in multiple-wave influenza outbreaks: Tristan da Cunha 1971 epidemic as a case study. Proceedings of the Royal Society of London, Series B, 278: 3635–3643. Link
 
C. Bretó and E. L. Ionides (2011) Compound Markov counting processes and their applications to modeling infinitesimally over-dispersed systems. Stochastic Processes and their Applications, 121: 2571–2591. Link
 
A. Bhadra, E. L. Ionides, K. Laneri, M. Pascual, M. Bouma, and R. C. Dhiman (2011) Malaria in northwest India: data analysis via partially observed stochastic differential equation models driven by Lévy noise. Journal of the American Statistical Association, 106: 440–451. Link
 
S. N. Wood (2010) Statistical inference for noisy nonlinear ecological dynamic systems. Nature, 466: 1102–1104. Link
 
T. Toni and M. P. H. Stumpf (2010) Simulation-based model selection for dynamical systems in systems and population biology. Bioinformatics, 26: 104–110. Link
 
K. Laneri, A. Bhadra, E. L. Ionides, M. Bouma, R. C. Dhiman, R. S. Yadav, and M. Pascual (2010) Forcing versus feedback: epidemic malaria and monsoon rains in northwest India. PLoS Computational Biology, 6: e1000898. Link
 
D. He, E. L. Ionides, and A. A. King (2010) Plug-and-play inference for disease dynamics: measles in large and small populations as a case study. Journal of the Royal Society, Interface, 7: 271–283. Link
 
A. Bhadra (2010) Discussion of ‘Particle Markov chain Monte Carlo methods’ by C. Andrieu, A. Doucet and R. Holenstein. Journal of the Royal Statistical Society, Series B, 72: 314–315. Link
 
C. Andrieu, A. Doucet, and R. Holenstein (2010) Particle Markov chain Monte Carlo methods. Journal of the Royal Statistical Society, Series B, 72: 269–342. Link
 
T. Toni, D. Welch, N. Strelkowa, A. Ipsen, and M. P. H. Stumpf (2009) Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems. Journal of the Royal Society, Interface, 6: 187–202. Link
 
G. Evensen (2009) Data Assimilation: The Ensemble Kalman Filter. Link
 
C. Bretó, D. He, E. L. Ionides, and A. A. King (2009) Time series analysis via mechanistic models. Annals of Applied Statistics, 3: 319–348. Link
 
A. A. King, E. L. Ionides, M. Pascual, and M. J. Bouma (2008) Inapparent infections and cholera dynamics. Nature, 454: 877–880. Link
 
X. Cai and Z. Xu (2007) K-leap method for accelerating stochastic simulation of coupled chemical reactions. Journal of Chemical Physics, 126: 074102. Link
 
D. C. Reuman, R. A. Desharnais, R. F. Costantino, O. S. Ahmad, and J. E. Cohen (2006) Power spectra reveal the influence of stochasticity on nonlinear population dynamics. Proceedings of the National Academy of Sciences of the U.S.A., 103: 18860–18865. Link
 
E. L. Ionides, C. Bretó, and A. A. King (2006) Inference for nonlinear dynamical systems. Proceedings of the National Academy of Sciences of the U.S.A., 103: 18438–18443. Link
 
B. E. Kendall, S. P. Ellner, E. McCauley, S. N. Wood, C. J. Briggs, W. M. Murdoch, and P. Turchin (2005) Population cycles in the pine looper moth: Dynamical tests of mechanistic hypotheses. Ecological Monographs, 75: 259–276. Link
 
M. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp (2002) A tutorial on particle filters for online nonlinear, non-Gaussian Bayesian tracking. IEEE Transactions on Signal Processing, 50: 174–188. Link
 
J. Liu and M. West (2001) Combining parameter and state estimation in simulation-based filtering. In: Sequential Monte Carlo Methods in Practice (edited by A. Doucet, N. de Freitas, and N. J. Gordon) 197–224.
 
J. L. Anderson (2001) An ensemble adjustment Kalman filter for data assimilation. Monthly Weather Review, 129: 2884–2903. Link
 
B. E. Kendall, C. J. Briggs, W. W. Murdoch, P. Turchin, S. P. Ellner, E. McCauley, R. M. Nisbet, and S. N. Wood (1999) Why do populations cycle? A synthesis of statistical and mechanistic modeling approaches. Ecology, 80: 1789–1805. Link
 
S. P. Ellner, B. A. Bailey, G. V. Bobashev, A. R. Gallant, B. T. Grenfell, and D. W. Nychka (1998) Noise and nonlinearity in measles epidemics: Combining mechanistic and statistical approaches to population modeling. American Naturalist, 151: 425–440. Link
 
C. Gouriéroux and A. Monfort (1997) Simulation-based Econometric Methods. Link
 
G. Evensen (1994) Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. Journal of Geophysical Research: Oceans, 99: 10143–10162. Link
 
D. T. Gillespie (1977) Exact stochastic simulation of coupled chemical reactions. Journal of Physical Chemistry, 81: 2340–2361. Link
 
 

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This software has been made possible by support from the U.S. National Science Foundation (Grants #EF-0545276, #EF-0430120), by the “Inference for Mechanistic Models” Working Group supported by the National Center for Ecological Analysis and Synthesis (a Center funded by N.S.F. (Grant #DEB-0553768), the University of California, Santa Barbara, and the State of California), and by the RAPIDD program of the Science & Technology Directorate, Department of Homeland Security and the Fogarty International Center, U.S. National Institutes of Health.