15 papers
Spatial function-on-function quantile regression
Eylul Fidan, Ufuk Beyaztas, Soutir Bandyopadhyay
This paper introduces a novel penalized spatial function-on-function quantile regression framework for analyzing spatially indexed functional data, bridging a critical gap between…
Robust spatial scalar-on-function regression: A Fisher-consistent redescending M-estimation approach
Muge Mutis, Ufuk Beyaztas, Han Lin Shang
We develop a Fisher-consistent redescending robust estimator for the spatial scalar-on-function regression model, where a scalar response depends on both a functional predictor and…
Correcting Measurement Error and Zero Inflation in Functional Covariates for Scalar-on-Function Quantile Regression
Caihong Qin, Lan Xue, Ufuk Beyaztas +4
Wearable devices collect time-varying biobehavioral data, offering opportunities to investigate how behaviors influence health outcomes. However, these data often contain measureme…
Penalized spatial function-on-function regression
Ufuk Beyaztas, Han Lin Shang, Gizel Bakicierler Sezer
The function-on-function regression model is fundamental for analyzing relationships between functional covariates and responses. However, most existing function-on-function regres…
Addressing zero-inflated and mis-measured functional predictors in scalar-on-function regression model
Heyang Ji, Lan Xue, Ufuk Beyaztas +4
Wearable devices are often used in clinical and epidemiological studies to monitor physical activity behavior and its influence on health outcomes. These devices are worn over mult…
MECfda: An R Package for Bias Correction Due to Measurement Error in Functional and Scalar Covariates in Scalar-on-Function Regression Models
Heyang Ji, Ufuk Beyaztas, Nicolas Escobar-Velasquez +6
Functional data analysis (FDA) deals with high-resolution data recorded over a continuum, such as time, space or frequency. Device-based assessments of physical activity or sleep a…