Nonparametric regression method for estimating the error variance in unistage sampling
Otieno, Romanus Odhiambo
Mwalili, Tobias Mbithi
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Nonparametric regression provides computationally intensive estimation of unknown finite population quantities. Such estimation can be more robust than inference tied to model based inference. A nonparametric procedure for estimating error variance is suggested. An empirical example is given to illustrate the performance of the derived estimator vis-a-vis the currently popular variance estimator in model based surveys.