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ABSTRACT We propose a new estimation method to estimate the nonparametric functions in additive models, where the response is subject to fixed censoring. Under some regularity conditions, we show that… Click to show full abstract
ABSTRACT We propose a new estimation method to estimate the nonparametric functions in additive models, where the response is subject to fixed censoring. Under some regularity conditions, we show that the proposed estimator is uniformly consistent with certain convergence rates. The simulation study shows that the proposed estimator performs well in finite sample sizes. We also analyze a dataset from an HIV study for an illustration.
Keywords:
additive models;
censored responses;
fixed censored;
models fixed;
estimation additive
Journal Title: Journal of Nonparametric Statistics
Year Published: 2018
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Journal Title: Journal of Nonparametric Statistics
Year Published: 2018
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!