Comparing Simulated and Measured Values Using Mean Squared Deviation and its Components

By Kazuhiko Kobayashi, M. Salam. 2000

628 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Nature and Landscape Conservation, Plant Science

View Paper: https://www.semanticscholar.org/paper/fadf22c3eb3199630b24c35bce9047c487213fa1

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In Artificial Intelligence

In Nature and Landscape Conservation

In Plant Science

Citations in the corpus

Multi-Metric Evaluation of the Models WARM, CropSyst, and WOFOST for Rice (2009, background): “Willmott, 1982) is a universalmeasure withmultiple interpretations and can be used to recognize the fluctuationof theestimates among thenmeasurements (Kobayashi and Salam, 2000).”
Large‐Area Maize Yield Forecasting Using Leaf Area Index Based Yield Model (2005, positive): “Crop Sci. 42:1547–1555. and 1.3 for sLAI) and the SDSD values (1.3 and 1.4 for Asrar, G., M. Fuchs, E.T. Kanemasu, and J.L. Hatfield.”
Predicting on-farm soybean yields in the pampas using CROPGRO-soybean (2007, methodology): “Moreover, as in our study only the 8% of the RMSE was attributed to the simulation of average and standard deviation of paddocks yield (SB and SDSD, respectively, Table 4), the actual inaccuracy introduced will be reduced to less than 2% if the goal is centred in assessing the average and risk of yi”
Bayesian calibration, comparison and averaging of six forest models, using data from Scots pine stands across Europe (2013, background): “It was recommended in particular to decompose likelihoods into terms for individual output variables and to decompose mean squared errors (MSE) into terms for bias, variance mismatch and phase-shift (Kobayashi and Salam, 2000).”
Modeling approaches to estimate effective leaf area index from aerial discrete-return LIDAR (2009, methodology): “Root mean square error (RMSE) was calculated according to the methodology in Kobayashi and Salam (2000) and hemispherical photograph estimates, which were the better predictors of LAI (see Section 3), were then used in subsequent analyses.”
Model Evaluation by Comparison of Model-Based Predictions and Measured Values (2003, methodology): “By contrast, all three of these models for the seven environments used inof the Kobayashi and Salam (2000) components are this study.symmetric and consequently unchanged.”
Individually tracked geese follow peaks of temperature acceleration during spring migration (2012, methodology): “We statistically compared predicted and observed arrival dates using the so-called ‘root mean square deviation’ (Kobayashi and Salam 2000)”