Some developments in semiparametric statistics. (English) Zbl 1211.62066
Summary: We describe the historical development of some parts of semiparametric statistics. The emphasis is on efficient estimation. We understand semiparametric models in the general sense of a model that is neither parametric nor nonparametric. We restrict attention to models with independent and identically distributed observations and to time series.
MSC:
| 62G08 | Nonparametric regression and quantile regression |
| 62M10 | Time series, auto-correlation, regression, etc. in statistics (GARCH) |
| 62F12 | Asymptotic properties of parametric estimators |
Keywords:
efficiency; convolution theorem; Newton-Raphson procedure; linear constraint; marginal constraint; symmetric location model; copula model, semiparametric regression; partly linear regression; nonparametric regression; conditional constraint; moving average; autoregression; linear process; prediction; quasi-likelihood model; estimating equation; local U-statisticReferences:
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