Results 1 to 10 of about 1,977,073 (168)

Introducing Robust Statistics in the Uncertainty Quantification of Nuclear Safeguards Measurements [PDF]

Entropy, 2022
The monitoring of nuclear safeguards measurements consists of verifying the coherence between the operator declarations and the corresponding inspector measurements on the same nuclear items.
Andrea Cerasa
doaj   +2 more sources

Robust Statistics [PDF]

, 2018
In lieu of an abstract, here is the entry\u27s first paragraph: Robust statistics are procedures that maintain nominal Type I error rates and statistical power in the presence of violations of the assumptions that underpin parametric inferential ...
Blaine, Bruce E
core   +6 more sources

Robust Statistics [PDF]

, 2011
The first example involves the real data given in Table 1 which are the results of an interlaboratory test. The boxplots are shown in Fig. 1 where the dotted line denotes the mean of the observations and the solid line the median.
Davies, P. Laurie, Gather, Ursula
core   +5 more sources

Robust Lifetime Estimation from HPGe Radiation-Sensor Time Series Using Pairwise Ratios and MFV Statistics [PDF]

Sensors
High-purity germanium (HPGe) gamma-ray detectors are core instruments in nuclear physics and astrophysics experiments, where long-term stability and reliable extraction of decay parameters are essential.
Victor V. Golovko
doaj   +2 more sources

Robust Trajectory Prediction for Mobile Robots via Minimum Error Entropy Criterion and Adaptive LSTM Networks [PDF]

Entropy
Trajectory prediction is critical for safe robot navigation, yet standard deep learning models predominantly rely on the Mean Squared Error (MSE) criterion.
Da Xie, Zengxun Li, Chun Zhang, Chunyang Wang, Xuyang Wei   +4 more
doaj   +2 more sources

On Robustness for Spatio-Temporal Data

Mathematics, 2022
The spatio-temporal variogram is an important factor in spatio-temporal prediction through kriging, especially in fields such as environmental sustainability or climate change, where spatio-temporal data analysis is based on this concept.
Alfonso García-Pérez
doaj   +1 more source

Geometric Morphometrics and Machine Learning Models Applied to the Study of Late Iron Age Cut Marks from Central Spain

Applied Sciences, 2023
Recently the incorporation of artificial intelligence has allowed the development of valuable methodological advances in taphonomy. Some studies have achieved great precision in identifying the carnivore that produced tooth marks.
Miguel Ángel Maté-González, Verónica Estaca-Gómez, Julia Aramendi, Cristina Sáez Blázquez, Jesús Rodríguez-Hernández, José Yravedra Sainz de los Terreros, Gonzalo Ruiz-Zapatero, Jesús R. Álvarez-Sanchís   +7 more
doaj   +1 more source

Robust Regression with Density Power Divergence: Theory, Comparisons, and Data Analysis

Entropy, 2020
Minimum density power divergence estimation provides a general framework for robust statistics, depending on a parameter α , which determines the robustness properties of the method. The usual estimation method is numerical minimization of the power
Marco Riani, Anthony C. Atkinson, Aldo Corbellini, Domenico Perrotta   +3 more
doaj   +1 more source

Outlier Detection for Support Vector Machine using Minimum Covariance Determinant Estimator [PDF]

Journal of Artificial Intelligence and Data Mining, 2019
The purpose of this paper is to identify the effective points on the performance of one of the important algorithm of data mining namely support vector machine.
M. Mohammadi, M. Sarmad
doaj   +1 more source

Statistical and Proactive Analysis of an Inter-Laboratory Comparison: The Radiocarbon Dating of the Shroud of Turin

Entropy, 2020
We review the sampling and results of the radiocarbon dating of the archaeological cloth known as the Shroud of Turin, in the light of recent statistical analyses of both published and raw data.
Paolo Di Lazzaro, Anthony C. Atkinson, Paola Iacomussi, Marco Riani, Marco Ricci, Peter Wadhams   +5 more
doaj   +1 more source