1 citations · 2 across the 7 of their papers we have counts for
12 papers
A robust scalar-on-function logistic regression for classification
Muge Mutis, Ufuk Beyaztas, Gulhayat Golbasi Simsek +1
Scalar-on-function logistic regression, where the response is a binary outcome and the predictor consists of random curves, has become a general framework to explore a linear relat…
A Robust Functional Partial Least Squares for Scalar-on-Multiple-Function Regression
Ufuk Beyaztas, Han Lin Shang
The scalar-on-function regression model has become a popular analysis tool to explore the relationship between a scalar response and multiple functional predictors. Most of the exi…
A robust partial least squares approach for function-on-function regression
Ufuk Beyaztas, Han Lin Shang
The function-on-function linear regression model in which the response and predictors consist of random curves has become a general framework to investigate the relationship betwee…
Function-on-function partial quantile regression
Ufuk Beyaztas, Han Lin Shang, Aylin Alin
In this paper, a functional partial quantile regression approach, a quantile regression analog of the functional partial least squares regression, is proposed to estimate the funct…
A functional autoregressive model based on exogenous hydrometeorological variables for river flow prediction
Ufuk Beyaztas, Han Lin Shang, Zaher Mundher Yaseen
In this research, a functional time series model was introduced to predict future realizations of river flow time series. The proposed model was constructed based on a functional t…
A partial least squares approach for function-on-function interaction regression
Ufuk Beyaztas, Han Lin Shang
A partial least squares regression is proposed for estimating the function-on-function regression model where a functional response and multiple functional predictors consist of ra…