Results 11 to 20 of about 1,079,927 (298)
Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not
Geoscientific Model Development, 2022 . The root-mean-squared error (RMSE) and mean absolute error (MAE) are widely used metrics for evaluating models. Yet, there remains enduring confusion over their use, such that a standard practice is to present both, leaving it to the reader to decide ...
T. Hodson
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Correcting the Bias of the Root Mean Squared Error of Approximation Under Missing Data
Methodology, 2021 Missing data are ubiquitous in psychological research. They may come about as an unwanted result of coding or computer error, participants' non-response or absence, or missing values may be intentional, as in planned missing designs.
Cailey E. Fitzgerald +4 more
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Multi-Agent Estimation and Filtering for Minimizing Team Mean-Squared Error [PDF]
IEEE Transactions on Signal Processing, 2019 Motivated by estimation problems arising in autonomous vehicles and decentralized control of unmanned aerial vehicles, we consider multi-agent estimation and filtering problems in which multiple agents generate state estimates based on decentralized ...
Mohammad Afshari, A. Mahajan
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Agriculture, 2022 To ensure continued food security and economic development in Africa, it is very important to address and adapt to climate change. Excessive dependence on rainfed agricultural production makes Africa more vulnerable to climate change effects.
Chimango Nyasulu +4 more
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Optimum thresholding using mean and conditional mean squared error [PDF]
Journal of Econometrics, 2017 We consider a univariate semimartingale model for (the logarithm of) an asset price, containing jumps having possibly infinite activity (IA). The nonparametric threshold estimator of the integrated variance IV proposed in Mancini 2009 is constructed ...
J. E. Figueroa-L'opez, C. Mancini
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Applied System Innovation, 2020 In the “Age of the Internet”, fake news and rumor-mongering have emerged as some of the most critical factors that affect our online social lives. For example, in the workplace, rumor spreading runs rampant during times when employees may be plagued with
Shih-Hsien Tseng, Tien Son Nguyen
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Frontiers in Psychology, 2022 Within the framework of constrained statistical inference, we can test informative hypotheses, in which, for example, regression coefficients are constrained to have a certain direction or be in a specific order. A large amount of frequentist informative
Caroline Keck, Axel Mayer, Yves Rosseel
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Interpolatory model reduction of dynamical systems with root mean squared error [PDF]
IFAC-PapersOnLineThe root mean squared error is an important measure used in a variety of applications such as structural dynamics and acoustics to model averaged deviations from standard behavior.
Sean Reiter, Steffen W. R. Werner
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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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Mean Squared Error Analysis of Quantizers With Error Feedback [PDF]
IEEE Transactions on Signal Processing, 2016 Quantization is a fundamental process in digital signal processing. $\Delta \Sigma$ modulators are often utilized for quantization, which can be easily implemented with static uniform quantizers and error feedback filters.
S. Ohno +3 more
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