Does model-free forecasting really outperform the true model?

Proceedings of the National Academy of Sciences of the United States of America

Volumn 110, Issue 42, 2013, Pages

  Hartig, Florian ^a   Dormann, Carsten F ^a  

^a UNIVERSITY OF FREIBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTICAL PARAMETERS; CHAOTIC DYNAMICS; FORECASTING; LETTER; POPULATION MODEL; PREDICTION; PRIORITY JOURNAL; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ECOSYSTEM; MODELS, BIOLOGICAL;

EID: 84885768828     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1308603110     Document Type: Letter

References (5)

1. Perretti CT, Munch SB, Sugihara G (2013) Model-free forecasting outperforms the correct mechanistic model for simulated and experimental data. Proc Natl Acad Sci USA 110(13): 5253-5257.
2. Pisarenko VF, Sornette D (2004) Statistical methods of parameter estimation for deterministically chaotic time series. Phys Rev E Stat Nonlin Soft Matter Phys 69(3 Pt 2): 036122.
3. Wood SN (2010) Statistical inference for noisy nonlinear ecological dynamic systems. Nature 466(7310): 1102-1104.
4. Judd K (2007) Failure of maximum likelihood methods for chaotic dynamical systems. Phys Rev E Stat Nonlin Soft Matter Phys 75(3 Pt 2): 036210.
5. Hartig F, Calabrese JM, Reineking B, Wiegand T, Huth A (2011) Statistical inference for stochastic simulation models - Theory and application. Ecol Lett 14(8): 816-827.