6 citations · 7 across the 7 of their papers we have counts for
4 papers · 1 filter
Pointwise Data Depth for Univariate and Multivariate Functional Outlier Detection
Cristian F. Jimenez-Varon, Fouzi Harrou, Ying Sun
Data depth is an efficient tool for robustly summarizing the distribution of functional data and detecting potential magnitude and shape outliers. Commonly used functional data dep…
Collective Spectral Density Estimation and Clustering for Spatially-Correlated Data
Tianbo Chen, Ying Sun, Mehdi Maadooliat
In this paper, we develop a method for estimating and clustering two-dimensional spectral density functions (2D-SDFs) for spatial data from multiple subregions. We use a common set…
A Semi-Parametric Estimation Method for the Quantile Spectrum with an Application to Earthquake Classification Using Convolutional Neural Network
Tianbo Chen, Ying Sun, Ta-Hsin Li
In this paper, a new estimation method is introduced for the quantile spectrum, which uses a parametric form of the autoregressive (AR) spectrum coupled with nonparametric smoothin…
Functional Outlier Detection and Taxonomy by Sequential Transformations
Wenlin Dai, Tomas Mrkvicka, Ying Sun +1
Functional data analysis can be seriously impaired by abnormal observations, which can be classified as either magnitude or shape outliers based on their way of deviating from the…