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20162024
most citedA robust functional time series forecasting method

8 citations · 10 across the 16 of their papers we have counts for

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21 papers · 1 filter

stat.ME20221 cited

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…

stat.ME20221 cited

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…

stat.ME2022

Clustering and Forecasting Multiple Functional Time Series

Chen Tang, Han Lin Shang, Yanrong Yang

Modelling and forecasting homogeneous age-specific mortality rates of multiple countries could lead to improvements in long-term forecasting. Data fed into joint models are often g…

stat.ME2021

Is the group structure important in grouped functional time series?

Yang Yang, Han Lin Shang

We study the importance of group structure in grouped functional time series. Due to the non-uniqueness of group structure, we investigate different disaggregation structures in gr…

stat.ME2021

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…

stat.ME2021

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…