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Semiparametric Comparison of Regression Curves
Open accessAbstract
The comparison of nonparametric regression curves is considered. It is assumed that there are parametric (possibly nonlinear) transformations of the axes which map one curve into the other. Estimation and testing of the parameters in the transformations are studied. The rate of convergence is $n^{-1/2}$ although the nonparametric components of the model typically have a rate slower than that. A statistic is provided for testing the validity of a given completely parametric model.
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Citations
Cited by
Alignment of curves by dynamic time warping
Wang, K., & Gasser, T. (1997) · The Annals of Statistics · doi:10.1214/aos/1069362747 · Cited by 293
Semiparametric estimates and tests of base-independent equivalence scales
Pendakur, K. (1999) · Journal of Econometrics · doi:10.1016/s0304-4076(98)00020-7 · Cited by 141
Semi‐parametric estimation of consumption‐based equivalence scales: the case of Germany
Wilke, R. A. (2006) · Journal of Applied Econometrics · doi:10.1002/jae.888 · Cited by 15
Metadata
- Authors
- Hardle, W., & Marron, J. S.
- Venue
- The Annals of Statistics
- Publisher
- Institute of Mathematical Statistics
- Published
- 1990-03-01
- Volume
- 18
- Issue
- 1
- ISSN
- 0090-5364 (ISSN-L)
- OpenAlex
- W2080558403
- Cited by
- 195
- References
- 0
- FWCI
- 7.66
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: Semiparametric Comparison of Regression Curves. https://app.cochat.ai/papers/10.1214/aos/1176347493
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- Hardle, W., & Marron, J. S. (1990). Semiparametric Comparison of Regression Curves. The Annals of Statistics. https://doi.org/10.1214/aos/1176347493
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
