11 papers
Quantifying Periodicity in Non-Euclidean Random Objects
Jiazhen Xu, Andrew T. A. Wood, Tao Zou
Time-varying non-Euclidean random objects are playing a growing role in modern data analysis, and periodicity is a fundamental characteristic of time-varying data. However, quantif…
Change Point Detection for Random Objects with Periodic Behavior
Jiazhen Xu, Andrew T. A. Wood, Tao Zou
Time-varying random objects have been increasingly encountered in modern data analysis. Moreover, in a substantial number of these applications, periodic behaviour of the random ob…
Quasi-Score Matching Estimation for Spatial Autoregressive Model with Random Weights Matrix and Regressors
Xuan Liang, Tao Zou
With the rapid advancements in technology for data collection, the application of the spatial autoregressive (SAR) model has become increasingly prevalent in real-world analysis, p…
Regularization and Selection in A Directed Network Model with Nodal Homophily and Nodal Effects
Zhaoyu Xing, Y. X. Rachel Wang, Andrew T. A. Wood +1
This article introduces a regularization and selection methods for directed networks with nodal homophily and nodal effects. The proposed approach not only preserves the statistica…
Subbagging Variable Selection for Big Data
Xian Li, Xuan Liang, Tao Zou
This article introduces a subbagging (subsample aggregating) approach for variable selection in regression within the context of big data. The proposed subbagging approach not only…
Robust Functional Principal Component Analysis for Non-Euclidean Random Objects
Jiazhen Xu, Andrew T. A. Wood, Tao Zou
Functional data analysis offers a diverse toolkit of statistical methods tailored for analyzing samples of real-valued random functions. Recently, samples of time-varying random ob…