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  • Search: person:"Wood, S. N."
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Wood, S. N. 7 Wood, S.N. 3 Clarke, E. D. 2 Clarke, E.D. 2 Demyanov, V. 2 Gurney, W. S. C. 2 Gurney, W.S.C. 2 Heath, M. R. 2 Heath, M.R. 2 Holmes, S. J. 2 Holmes, S.J. 2 Speirs, D. C. 2 Speirs, D.C. 2 Kedwards, T. J. 1 Kedwards, T.J. 1
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Journal of the Royal Statistical Society / C 3 Journal of the Royal Statistical Society Series C 3 Journal of the Royal Statistical Society Series B 1
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RePEc 4 BASE 3 OLC EcoSci 3
Showing 1 - 10 of 10
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Stable and efficient multiple smoothing parameter estimation for generalized additive models
Wood, S. N. - 2004
Representation of generalized additive models (GAM's) using penalized regression splines allows GAM's to be employed in a straightforward manner using penalized regression methods. Not only is inference facilitated by this approach, but it is also possible to integrate model selection in the...
Persistent link: https://www.econbiz.de/10009428608
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Partially specified ecological models
Wood, S. N. - 2001
Models are useful when they are compared with data. Whether this comparison should be qualitative or quantitative depends on circumstances, but in many cases some statistical comparison of model and data is useful and enhances objectivity. Unfortunately, ecological dynamic models tend to contain...
Persistent link: https://www.econbiz.de/10009428648
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Minimizing model fitting objectives that contain spurious local minima by bootstrap restarting
Wood, S. N. - 2001
Objective functions that arise when fitting nonlinear models often contain local minima that are of little significance except for their propensity to trap minimization algorithms. The standard methods for attempting to deal with this problem treat the objective function as fixed and employ...
Persistent link: https://www.econbiz.de/10009428649
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Improving ecological impact assessment by statistical data synthesis using process-based models
Demyanov, V.; Wood, S. N.; Kedwards, T. J. - In: Journal of the Royal Statistical Society Series C 55 (2006) 1, pp. 41-62
Population dynamic modelling often entails parameterizing quite sophisticated biological and ecological mechanisms. For models of moderate mechanistic complexity, this has traditionally been done in an "ad hoc" manner, with different parameters being estimated independently. The point estimates...
Persistent link: https://www.econbiz.de/10005217102
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Calibrating remotely sensed chlorophyll-a data by using penalized regression splines
Clarke, E. D.; Speirs, D. C.; Heath, M. R.; Wood, S. N.; … - In: Journal of the Royal Statistical Society Series C 55 (2006) 3, pp. 331-353
The distribution and biomass of phytoplankton in the upper layers of the ocean are important indicators of productivity and carbon cycling. Large scale perturbations in phytoplankton are linked to global climate change, so accurate monitoring is increasingly important. The chlorophyll-a pigment...
Persistent link: https://www.econbiz.de/10005309372
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Corrigendum: Calibrating remotely sensed chlorophyll-a data by using penalized regression splines
Clarke, E. D.; Speirs, D. C.; Heath, M. R.; Wood, S. N.; … - In: Journal of the Royal Statistical Society Series C 55 (2006) 4, pp. 551-552
Persistent link: https://www.econbiz.de/10005162155
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Corrigendum: Calibrating remotely sensed chlorophyll-a data by using penalized regression splines
Clarke, E.D.; Speirs, D.C.; Heath, M.R.; Wood, S.N.; … - In: Journal of the Royal Statistical Society / C 55 (2006) 4, pp. 551
Persistent link: https://www.econbiz.de/10008222505
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Calibrating remotely sensed chlorophyll-a data by using penalized regression splines
Clarke, E.D.; Speirs, D.C.; Heath, M.R.; Wood, S.N.; … - In: Journal of the Royal Statistical Society / C 55 (2006) 3, pp. 331-354
Persistent link: https://www.econbiz.de/10008222721
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Improving ecological impact assessment by statistical data synthesis using process-based models
Demyanov, V.; Wood, S.N.; Kedwards, T.J. - In: Journal of the Royal Statistical Society / C 55 (2006) 1, pp. 41-62
Persistent link: https://www.econbiz.de/10008222869
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Modelling and smoothing parameter estimation with multiple quadratic penalties
Wood, S. N. - In: Journal of the Royal Statistical Society Series B 62 (2000) 2, pp. 413-428
Persistent link: https://www.econbiz.de/10005140202
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