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arXiv · 2510.21661

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·Yuanyuan Luan·Xiwei Chen·Mengli Zhang·Roger Zoh·Lan Xue·Carmen Tekwe
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Abstract

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 are objective yet still prone to measurement error. We present MECfda, an R package that (i) fits scalar-on-function, generalized scalar-on-function, and functional quantile regression models, and (ii) provides bias-corrected estimation when functional covariates are measured with error. By unifying these tools under a consistent syntax, MECfda enables robust inference for FDA applications that involve noisy functional data.

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Heyang Ji, Ufuk Beyaztas, Nicolas Escobar-Velasquez, Yuanyuan Luan, Xiwei Chen, Mengli Zhang, Roger Zoh, Lan Xue, Carmen Tekwe. 2025-10-24. MECfda: An R Package for Bias Correction Due to Measurement Error in Functional and Scalar Covariates in Scalar-on-Function Regression Models. https://arxiv.org/abs/2510.21661

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