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The method of sieves and minimum contrast estimators. (English) Zbl 0831.62029
Summary: We set up a general framework for sieves in the context of minimum contrast estimation. This makes it possible to compare several methods and goals (such as overcoming a diverging entropy integral or a non- compact parameter space). We are only concerned with rates of convergence. As examples, we discuss least squares and maximum likelihood estimators, and in more detail, splines and interval censored observations.

MSC:
62G05 Nonparametric estimation
62G30 Order statistics; empirical distribution functions
62G20 Asymptotic properties of nonparametric inference
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