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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.21661 |
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| _version_ | 1866915581542793216 |
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| author | Ji, Heyang Beyaztas, Ufuk Escobar-Velasquez, Nicolas Luan, Yuanyuan Chen, Xiwei Zhang, Mengli Zoh, Roger Xue, Lan Tekwe, Carmen |
| author_facet | Ji, Heyang Beyaztas, Ufuk Escobar-Velasquez, Nicolas Luan, Yuanyuan Chen, Xiwei Zhang, Mengli Zoh, Roger Xue, Lan Tekwe, Carmen |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_21661 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | MECfda: An R Package for Bias Correction Due to Measurement Error in Functional and Scalar Covariates in Scalar-on-Function Regression Models Ji, Heyang Beyaztas, Ufuk Escobar-Velasquez, Nicolas Luan, Yuanyuan Chen, Xiwei Zhang, Mengli Zoh, Roger Xue, Lan Tekwe, Carmen Methodology Computation 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. |
| title | MECfda: An R Package for Bias Correction Due to Measurement Error in Functional and Scalar Covariates in Scalar-on-Function Regression Models |
| topic | Methodology Computation |
| url | https://arxiv.org/abs/2510.21661 |