论文信息 - A bootstrap theorem for a preliminary test estimator

A bootstrap theorem for a preliminary test estimator

A preliminary test estimator is a method of combining information from two experiments by pooling estimators. The asymptotics of this estimator in the case of estimating a population mean is considered, in a setting of a local alternative. In addition the question of using a bootstrap technique in the same setting is considered. It is shown that the bootstrap technique using empirical distributions does not give the correct asymptotic distribution.

S. E. Ahmed | R. Kulperger | R. J. Kulperger | S. Ahmed

[1] William Feller,et al. An Introduction to Probability Theory and Its Applications , 1967 .

[2] S. E. Ahmed. To pool or not to pool: The discrete data , 1991 .

[3] T. A. Bancroft,et al. On Pooling Means when Variance is Unknown , 1968 .

[4] Frederick Mosteller,et al. On Pooling Data , 1948 .

[5] Pranab Kumar Sen,et al. Nonparametric Estimation of Location Parameter After a Preliminary Test on Regression , 1978 .

[6] Combining poisson means , 1991 .

[7] T. A. Bancroft,et al. On Biases in Estimation Due to the Use of Preliminary Tests of Significance , 1944 .

[8] J. Ravichandran,et al. Inference based on conditional speclfication , 1988 .

[9] B. Efron. Bootstrap Methods: Another Look at the Jackknife , 1979 .