Some topics in nonparametric inference
In Chapters 9, 10, 11, and 12, we concerned ourselves with the question of point estimation, interval estimation, and testing hypotheses about (most of the time) a real-valued parameter θ. This inference was hedged on the basic premise that we were able to stipulate each time a probability model, which was completely known except for a parameter θ (real-valued or of higher dimension).
The natural question which arises is this: What do we do, if there is no sound basis for the stipulation of a probability model from which the observations are drawn? In such a situation, we don't have parametric inference problems to worry about, because, simply, we don't have a parametric model. In certain situations ...
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