Statistical inference for a varying-coefficient partially nonlinear model with measurement errors
| Autor: | Zhensheng Huang, Yunyun Qian |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Statistics and Probability
Mathematical optimization Observational error Current (mathematics) 05 social sciences Nonparametric statistics Asymptotic distribution 01 natural sciences 010104 statistics & probability Nonlinear model Likelihood-ratio test 0502 economics and business Statistical inference Applied mathematics 0101 mathematics Constant (mathematics) 050205 econometrics Mathematics |
| Zdroj: | Statistical Methodology. 32:122-130 |
| ISSN: | 1572-3127 |
| Popis: | In this study a varying-coefficient partially nonlinear model with measurement errors in the nonparametric part is proposed. Based on the corrected profile least-squared estimation methodology, we define the estimates of the unknowns of the current models, and check whether the coefficient functions are a constant or not by using the popular generalized likelihood ratio (GLR) test method. Further, the corresponding asymptotic distribution is established and a bootstrap procedure is also employed to implement the proposed methodology. Simulated and real examples are given to illustrate our proposed methodology. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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