Results 11 to 20 of about 1,990,709 (285)
Robust Statistics for Image Deconvolution [PDF]
Astronomy and Computing, 2017 We present a blind multiframe image-deconvolution method based on robust statistics. The usual shortcomings of iterative optimization of the likelihood function are alleviated by minimizing the M-scale of the residuals, which achieves more uniform ...
Budavari, Tamas +3 more
core +2 more sources
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
Anomaly Detection by Robust Statistics [PDF]
WIREs Data Mining and Knowledge Discovery, 2017 Real data often contain anomalous cases, also known as outliers. These may spoil the resulting analysis but they may also contain valuable information. In either case, the ability to detect such anomalies is essential.
Hubert, Mia, Rousseeuw, Peter J.
core +3 more sources
, 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
, 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 Lifetime Estimation from HPGe Radiation-Sensor Time Series Using Pairwise Ratios and MFV Statistics [PDF]
SensorsHigh-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 statistics: a functional approach [PDF]
, 2012 International audienceFor a given statistical method, good properties are usually obtained under strong hypotheses that are likely not to be verified in practice.
Ruiz-Gazen, Anne
core +5 more sources
Robust Trajectory Prediction for Mobile Robots via Minimum Error Entropy Criterion and Adaptive LSTM Networks [PDF]
EntropyTrajectory prediction is critical for safe robot navigation, yet standard deep learning models predominantly rely on the Mean Squared Error (MSE) criterion.
Da Xie +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
Ambiguity and robust statistics [PDF]
Journal of Economic Theory, 2013 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cerreia-Vioglio, Simone +3 more
openaire +2 more sources