Reply to Hartig and Dormann: The true model myth

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

Volumn 110, Issue 42, 2013, Pages

  Perretti, Charles T ^a   Munch, Stephan B ^b   Sugihara, George ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b SOUTHWEST FISHERIES SCIENCE CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTICAL ERROR; DYNAMICS; ECOLOGY; ECOSYSTEM; ENVIRONMENTAL MANAGEMENT; FORECASTING; HUMAN; LETTER; LOGISTIC REGRESSION ANALYSIS; PARAMETERS; PRIORITY JOURNAL; SIMULATION; STATISTICAL ANALYSIS; TIME SERIES ANALYSIS; WILDLIFE CONSERVATION;

ECOSYSTEM; MODELS, BIOLOGICAL;

EID: 84885693004     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1312461110     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. Hartig F, Dormann CF (2013) Does model-free forecasting really outperform the true model? Proc Natl Acad Sci USA 110:E3975.
3. 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.
4. Perretti CT, Sugihara G, Munch SB (2013) Nonparametric forecasting outperforms parametric methods for a simulated multispecies system. Ecology 94(4): 794-800.
5. Sugihara G, et al. (2012) Detecting causality in complex ecosystems. Science 338(6106): 496-500.