2 citations · 2 across the 9 of their papers we have counts for
9 papers
Quantifying Long-Range Dependence in Object-Valued Time Series
Won-Ki Seo, Jiazhen Xu, Han Lin Shang
Object-valued time series, including distributions, covariance matrices, networks, and compositions, lack the linear structure required by conventional autocovariance-based definit…
Uniform Convergence of Generalized Conditional Fréchet Means with Applications to Weighted Fréchet Aggregation and Exceedance Set Estimation
Houren Hong, Jiazhen Xu, Andrew T. A. Wood
The statistical analysis of object oriented data in non-Euclidean spaces heavily relies on generalized conditional Fréchet means, notably in the context of Fréchet regression. Howe…
Spherically Embedded Time Series with Unknown Trend and Periodic Components
Jiazhen Xu, Han Lin Shang
Spherically embedded time series are time series with values naturally residing on or can be equivalently mapped to the sphere. Despite their ubiquity in diverse scientific fields,…
Spherical Spatial Autoregressive Model for Spherically Embedded Spatial Data
Jiazhen Xu, Han Lin Shang
Spherically embedded spatial data are spatially indexed observations whose values naturally reside on or can be equivalently mapped to the unit sphere. Such data are increasingly u…
Quantifying Periodicity in Non-Euclidean Object-Valued Time Series
Jiazhen Xu, Andrew T. A. Wood, Tao Zou
Non-Euclidean object-valued time series are playing a growing role in modern data analysis, and periodicity is a fundamental characteristic of many time series. However, quantifyin…
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…
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…
Generalized Score Matching
Jiazhen Xu, Janice L. Scealy, Andrew T. A. Wood +1
Score matching is an estimation procedure that has been developed for statistical models whose probability density function is known up to proportionality but whose normalizing con…
Generalized Score Matching for Regression
Jiazhen Xu, Janice L. Scealy, Andrew T. A. Wood +1
Many probabilistic models that have an intractable normalizing constant may be extended to contain covariates. Since the evaluation of the exact likelihood is difficult or even imp…