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Ensemble averaging and mean squared error [PDF]
Journal of Climate, 2016 In fields such as climate science, it is common to compile an ensemble of different simulators for the same underlying process. It is a striking observation that the ensemble mean often outperforms at least half of the ensemble members in mean squared ...
Rougier, Jonathan
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Exact Mean Integrated Squared Error [PDF]
The Annals of Statistics, 1992 An exact and easily computable expression for the mean integrated squared error (MISE) for the kernel estimator of a general normal mixture density, is given for Gaussian kernels of arbitrary order. This provides a powerful new way of understanding density estimation which complements the usual tools of simulation and asymptotic analysis. The family of
J. S. Marron, M. P. Wand
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Optimal Mean Squared Error Imaging [PDF]
AIAA Guidance, Navigation, and Control Conference and Exhibit, 2002 Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77345/1/AIAA-2002-4952-350 ...
Suman Chakravorty +2 more
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Mean Squared Error, Deconstructed [PDF]
Journal of Advances in Modeling Earth Systems, 2021 AbstractAs science becomes increasingly cross‐disciplinary and scientific models become increasingly cross‐coupled, standardized practices of model evaluation are more important than ever. For normally distributed data, mean squared error (MSE) is ideal as an objective measure of model performance, but it gives little insight into what aspects of model
Timothy O. Hodson +2 more
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Mean squared error of empirical predictor [PDF]
The Annals of Statistics, 2004 The term ``empirical predictor'' refers to a two-stage predictor of a linear combination of fixed and random effects. In the first stage, a predictor is obtained but it involves unknown parameters; thus, in the second stage, the unknown parameters are ...
Das, Kalyan +2 more
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IX. On the Probable Error of Mean-Square Contingency [PDF]
Biometrika, 1906 n ...
J. BLAKEMAN, Karl Pearson
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Bootstrap for estimating the mean squared error of the spatial EBLUP [PDF]
, 2007 This work assumes that the small area quantities of interest follow a Fay-Herriot model with spatially correlated random area effects. Under this model, parametric and nonparametric bootstrap procedures are proposed for estimating the mean squared ...
Molina, Isabel +2 more
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Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation [PDF]
International Joint Conference on Artificial Intelligence, 2021 Knowledge distillation (KD), transferring knowledge from a cumbersome teacher model to a lightweight student model, has been investigated to design efficient neural architectures.
Taehyeon Kim +4 more
semanticscholar +1 more source
Optimizing LSTM Models for EUR/USD Prediction in the context of reducing energy consumption: An Analysis of Mean Squared Error, Mean Absolute Error and R-Squared [PDF]
E3S Web of Conferences, 2023 The purpose of this study was to develop and evaluate a Long Short-Term Memory (LSTM) model for Forex prediction. The data used was reprocessed and the LSTM model was developed and trained using a supervised learning approach with popular deep learning ...
Echrigui Rania, Hamiche Mhamed
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BREXIT Election:Forecasting a Conservative Party Victory through the Pound using ARIMA and Facebook\u27s Prophet [PDF]
, 2020 On the 30th October, 2019, the markets watched as British Prime Minister, Boris Johnson, took a massive political gamble to call a general election to break the Withdrawal Agreement stalemate in the House of Commons to “Get BREXIT Done”.
Makridakis +4 more
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