| Records |
| Author |
Rodríguez, A. |
Title  |
El uso de Superficies de Respuesta para el análisis de la adaptación de los cultivos al cambio climático y la incertidumbre asociada |
Type |
Book Whole |
| Year |
2016 |
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Thesis |
Master's thesis |
| Publisher |
Universidad de Castilla-La Mancha |
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MSc. |
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CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5159 |
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| Author |
Wilson, A. |
| Title |
Emerging infectious disease challenges |
Type |
Conference Article |
| Year |
2016 |
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STAR-IDAZ (Global Strategic Alliances for the Coordination of Research on the Major Infectious Diseases of Animals and Zoonoses) Foresight workshop on Emerging Infectious Disease Challenges, 2014-06-16 to 2014-06-16 |
| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4895 |
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| Author |
Bartley, D.J.; Skuce, P.J.; Zadoks, R.N.; MacLeod, M. |
| Title |
Endemic sheep and cattle diseases and greenhouse gas emissions |
Type |
Journal Article |
| Year |
2016 |
Publication |
Advances in Animal Biosciences |
Abbreviated Journal |
Advances in Animal Biosciences |
| Volume |
7 |
Issue |
03 |
Pages |
253-255 |
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| ISSN |
2040-4700 |
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| Notes |
LiveM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4865 |
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| Author |
Wallach, D.; Thorburn, P.; Asseng, S.; Challinor, A.J.; Ewert, F.; Jones, J.W.; Rötter, R.; Ruane, A. |
| Title |
Estimating model prediction error: Should you treat predictions as fixed or random |
Type |
Journal Article |
| Year |
2016 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
| Volume |
84 |
Issue |
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Pages |
529-539 |
| Keywords |
Crop model; Uncertainty; Prediction error; Parameter uncertainty; Input uncertainty; Model structure uncertainty |
| Abstract |
Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEPfixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEPuncertain(X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEPuncertain(X) can be estimated using a random effects ANOVA. It is argued that MSEPuncertain(X) is the more informative uncertainty criterion, because it is specific to each prediction situation. |
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English |
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| ISSN |
1364-8152 |
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Article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4773 |
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| Author |
Mestdagh, M. |
| Title |
Estimation du contenu en chlorophylle de la pomme de terre par télédétection hyperspectrale aéroportée |
Type |
Book Whole |
| Year |
2016 |
Publication |
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Abbreviated Journal |
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Issue |
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Pages |
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Thesis |
Master's thesis |
| Publisher |
Université Catholique de Louvain |
Place of Publication |
Louvain |
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M.Sc. |
| Series Volume |
M.Sc. |
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| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5160 |
| Permanent link to this record |
