5 papers
Spatial function-on-function regression
Ufuk Beyaztas, Han Lin Shang, Gizel Bakicierler Sezer +3
We introduce a spatial function-on-function regression model to capture spatial dependencies in functional data by integrating spatial autoregressive techniques with functional pri…
Clustering functional data with measurement errors: a simulation-based approach
Tingyu Zhu, Lan Xue, Carmen Tekwe +3
Clustering analysis of functional data, which comprises observations that evolve continuously over time or space, has gained increasing attention across various scientific discipli…
Adjusting for bias due to measurement error in functional quantile regression models with error-prone functional and scalar covariates
Xiwei Chen, Yuanyuan Luan, Roger S. Zoh +3
Wearable devices enable the continuous monitoring of physical activity (PA) but generate complex functional data with poorly characterized errors. Most work on functional data view…
Generalized functional linear regression models with a mixture of complex function-valued and scalar-valued covariates prone to measurement error
Yuanyuan Luan, Roger S. Zoh, Sneha Jadhav +2
While extensive work has been done to correct for biases due to measurement error in scalar-valued covariates prone to errors in generalized linear regression models, limited work…
A Bayesian Semi-Parametric Scalar-On-Function Quantile Regression with Measurement Error using the GAL
Roger S. Zoh, Annie Yu, Carmen Tekwe
Quantile regression provides a consistent approach to investigating the association between covariates and various aspects of the distribution of the response beyond the mean. When…