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Ensemble averaging and mean squared error [PDF]

open access: yesJournal 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
core   +6 more sources

Exact Mean Integrated Squared Error [PDF]

open access: bronzeThe 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
semanticscholar   +5 more sources

Optimal Mean Squared Error Imaging [PDF]

open access: greenAIAA 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
core   +4 more sources

Mean Squared Error, Deconstructed [PDF]

open access: yesJournal 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
openaire   +3 more sources

Mean squared error of empirical predictor [PDF]

open access: yesThe 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
core   +5 more sources

Bootstrap for estimating the mean squared error of the spatial EBLUP [PDF]

open access: yes, 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
core   +8 more sources

Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation [PDF]

open access: yesInternational 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]

open access: yesE3S 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
doaj   +1 more source

BREXIT Election:Forecasting a Conservative Party Victory through the Pound using ARIMA and Facebook\u27s Prophet [PDF]

open access: yes, 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
core   +2 more sources

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