Robust smoothing of gridded data in one and higher dimensions with missing values

By Damien Garcia. Computational Statistics & Data Analysis, 2010

1,082 citations recorded by the source corpus.

Subfields: Applied Mathematics, Civil and Structural Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/ac93a8c601c928d003c739ef7525b1748fc8dbb8

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In Applied Mathematics

In Civil and Structural Engineering

In Statistics and Probability

Citations in the corpus

Tests for separability in nonparametric covariance operators of random surfaces (2015, methodology): “The raw log-spectrograms S L ik are then smoothed [with the robust spline smoothing method proposed in Garcia (2010)] and aligned in time using an adaptation to 2-”
PIVlab – Towards User-friendly, Affordable and Accurate Digital Particle Image Velocimetry in MATLAB (2014, methodology): “More advanced smoothing algorithms are based on a penalized least squares method [28] – the latter technique is implemented in PIVlab.”
Rotating waves during human sleep spindles organize global patterns of activity that repeat precisely through the night (2016, methodology): “The phase fields were then smoothed using a robust approach (Garcia, 2010) for center localization to reduce noise and interpolate values from missing electrodes; note that the smoothed values were not used in the calculations for detecting expanding and rotational wave patterns.”
PLANETARY CANDIDATES OBSERVED BY KEPLER. VI. PLANET SAMPLE FROM Q1–Q16 (47 MONTHS) (2015, methodology): “We employ the non-parametric penalized least squares method from Garcia (2010) which includes only the out-of-transit points when computing the filter.”
Deep Depth Completion of a Single RGB-D Image (2018, methodology): “In this additional study, we compare with the following methods: • DCT [23]: ﬁll in missing values by solving the penalized least squares of a linear system using discrete cosine transform using the code from Matlab Central .”