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Improved estimators of regression coefficients in measurement error models
Abstract:This paper is concerned with methods of reducing variability and computer time in a simulation study. The Monte Carlo swindle, through mathematical manipulations, has been shown to yield more precise estimates than the “naive” approach. In this study computer time is considered in conjunction with the variance estimates. It is shown that by this measure the naive method is often a viable alternative to the swindle. This study concentrates on the problem of estimating the variance of an estimator of location. The advantage of one technique over another depends upon the location estimator, the sample size, and the underlying distribution. For a fixed number of samples, while the naive method gives a less precise estimate than the swindle, it requires fewer computations. In addition, for certain location estimators and distributions, the naive method is able to take advantage of certain shortcuts in the generation of each sample. The small amount of time required by this “enlightened” naive method often more than compensates for its relative lack of precision.
Keywords:Monte Carlo Methods  Simulation  Variance-Reducation
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