33 citations · 47 across the 26 of their papers we have counts for
11 papers · 1 filter
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…
Spatial Scalar-on-Function Quantile Regression Model
Muge Mutis, Ufuk Beyaztas, Filiz Karaman +1
This paper introduces a novel spatial scalar-on-function quantile regression model that extends classical scalar-on-function models to account for spatial dependence and heterogene…
Robust Functional Logistic Regression
Berkay Akturk, Ufuk Beyaztas, Han Lin Shang
Functional logistic regression is a popular model to capture a linear relationship between binary response and functional predictor variables. However, many methods used for parame…
On function-on-function linear quantile regression
Muge Mutis, Ufuk Beyaztas, Filiz Karaman +1
We present two innovative functional partial quantile regression algorithms designed to accurately and efficiently estimate the regression coefficient function within the function-…
Least squares-based methods to bias adjustment in scalar-on-function regression model using a functional instrumental variable
Xiwei Chen, Ufuk Beyaztas, Caihong Qin +5
Instrumental variables are widely used to adjust for measurement error bias when assessing associations of health outcomes with ME prone independent variables. IV approaches addres…
Spatial Functional Deep Neural Network Model: A New Prediction Algorithm
Merve Basaran, Ufuk Beyaztas, Han Lin Shang +1
Accurate prediction of spatially dependent functional data is critical for various engineering and scientific applications. In this study, a spatial functional deep neural network…
Stock Return Prediction based on a Functional Capital Asset Pricing Model
Ufuk Beyaztas, Kaiying Ji, Han Lin Shang +1
The capital asset pricing model (CAPM) is readily used to capture a linear relationship between the daily returns of an asset and a market index. We extend this model to an intrada…
Penalized function-on-function linear quantile regression
Ufuk Beyaztas, Han Lin Shang, Semanur Saricam
We introduce a novel function-on-function linear quantile regression model to characterize the entire conditional distribution of a functional response for a given functional predi…
Functional Linear Cox Regression Model with Frailty
Deniz Inan, Ufuk Beyaztas, Carmen D. Tekwe +2
This paper presents a functional linear Cox regression model with frailty to tackle unobserved heterogeneity in survival data with functional covariates. While traditional Cox mode…