Name
Abstract | ||
|---|---|---|
This paper considers estimation and testing problems for partial functional linear models when the covariates in the non-functional linear component are measured with additive error. A corrected profile, least-squares based, estimation procedure is developed for the parametric component. Asymptotic properties of the proposed estimators are established under some regularity conditions. To test a hypothesis on the parametric component, a statistic based on the difference between the corrected residual sums of squares under the null and alternative hypotheses is proposed; its limiting null distribution is shown to be a weighted sum of independent standard χ12 variables. Simulation studies are conducted to demonstrate the performance of the proposed procedure and a real example is analyzed for illustration. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.jmva.2018.11.005 | Journal of Multivariate Analysis |
Keywords | Field | DocType |
Corrected profile least-squares,Errors-in-variables,Functional data,Hypothesis test,Partially linear models | Errors-in-variables models,Alternative hypothesis,Statistic,Linear model,Parametric statistics,Statistics,Statistical hypothesis testing,Null distribution,Mathematics,Estimator | Journal |
Volume | ISSN | Citations |
170 | 0047-259X | 3 |
PageRank | References | Authors |
0.44 | 8 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hanbing Zhu | 1 | 3 | 0.44 |
| Riquan Zhang | 2 | 52 | 21.55 |
| Zhou Yu | 3 | 7 | 3.08 |
| Heng Lian | 4 | 4 | 1.16 |
| Yanghui Liu | 5 | 3 | 0.78 |