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Bootstrapping the Mean Integrated Squared Error
Journal of Multivariate Analysis, 1993 Let \(X_ 1,\dots,X_ n\) be a sequence of i.i.d. real random variables from an unknown density \(f\). For a given kernel \(K\) and a bandwidth \(h>0\), denote with \(f_ h\) the associated Parzen-Rosenblatt estimator of \(f\). There exists a huge literature on how to choose \(h\) in an optimal way.
Cao, R.
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Developing Novel Robust Loss Functions-Based Classification Layers for DLLSTM Neural Networks
IEEE Access, 2023 In this paper, we suggest improving the performance of developed activation function-based Deep Learning Long Short-Term Memory (DLLSTM) structures by employing robust loss functions like Mean Absolute Error $(MAE)$ and Sum Squared Error $(SSE)$ to ...
Mohamad Abou Houran +5 more
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New robust iterative minimum mean squared error-based interference alignment algorithm
The Journal of Engineering, 2014 Interference alignment (IA) is a promising technique for multiple input multiple output interference channels based systems, achieving the theoretical bound on degrees of freedom.
Sara Teodoro +4 more
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Defense of the Least Squares Solution to Peelle’s Pertinent Puzzle
Algorithms, 2011 Generalized least squares (GLS) for model parameter estimation has a long and successful history dating to its development by Gauss in 1795. Alternatives can outperform GLS in some settings, and alternatives to GLS are sometimes sought when GLS exhibits ...
Nicolas Hengartner +4 more
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Mid-Term Residential Load Forecasting Based on Neighborhood Component Analysis Feature Selection [PDF]
هوش محاسباتی در مهندسی برق, 2022 Residential load forecasting plays an important role in management and planning in modern smart grids. In planning to keep demand and supply balanced, accurate residential load forecasting is needed.
Iman Bahadornejad +4 more
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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 ...
Pratesi, Monica +2 more
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Evaluating Gaussian processes for matched-field processing localization using minimum mean squared error criterion [PDF]
JASA Express LettersGaussian processes (GPs) can densify and denoise sparsely sampled signals and have been applied in matched-field processing (MFP) localization to improve localization accuracy and robustness.
Shanru Lin +4 more
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Load Forecasting Techniques for Power System: Research Challenges and Survey
IEEE Access, 2022 The main and pivot part of electric companies is the load forecasting. Decision-makers and think tank of power sectors should forecast the future need of electricity with large accuracy and small error to give uninterrupted and free of load shedding ...
Naqash Ahmad +3 more
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Data Science Journal, 2010 An alternative ratio-cum-product estimator of population mean using the coefficient of kurtosis for two auxiliary variates has been proposed. The proposed estimator has been compared with a simple mean estimator, the usual ratio estimator, a product ...
Rajesh Tailor +2 more
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Exact Mean Integrated Squared Error
The Annals of Statistics, 1992 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Marron, J. S., Wand, M. P.
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