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Semi-supervised estimation for the varying coefficient regression model
- Source :
- AIMS Mathematics, Vol 9, Iss 1, Pp 55-72 (2024)
- Publication Year :
- 2024
- Publisher :
- AIMS Press, 2024.
-
Abstract
- In many cases, the 'labeled' outcome is difficult to observe and may require a complicated or expensive procedure, and the predictor information is easy to be obtained. We propose a semi-supervised estimator for the one-dimensional varying coefficient regression model which improves the conventional supervised estimator by using the unlabeled data efficiently. The semi-supervised estimator is proposed by introducing the intercept model and its asymptotic properties are proven. The Monte Carlo simulation studies and a real data example are conducted to examine the finite sample performance of the proposed procedure.
Details
- Language :
- English
- ISSN :
- 24736988
- Volume :
- 9
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- AIMS Mathematics
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.bb9abb1a632945278e4cf6393fac4da2
- Document Type :
- article
- Full Text :
- https://doi.org/10.3934/math.2024004?viewType=HTML