To show that an estimator can be consistent withoutbeing unbiased or even asymptotically unbiased, considerthe following estimation procedure: To estimate the meanof a population with the finite variance σ2, we first takea random sample of size n. Then we randomly draw oneof n slips of paper numbered from 1 through n, and if thenumber we draw is 2, 3, ..., or n, we use as our estimator the mean of the random sample; otherwise, we use theestimate n2. Show that this estimation procedure is(a) consistent;(b) neither unbiased nor asymptotically unbiased.
To show that an estimator can be consistent withoutbeing unbiased or even asymptotically unbiased, considerthe following estimation procedure: To estimate the meanof a population with the finite variance σ2, we first takea random sample of size n. Then we randomly draw oneof n slips of paper numbered from 1 through n, and if thenumber we draw is 2, 3, ..., or n, we use as our estimator the mean of the random sample; otherwise, we use theestimate n2. Show that this estimation procedure is(a) consistent;(b) neither unbiased nor asymptotically unbiased.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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To show that an estimator can be consistent without
being unbiased or even asymptotically unbiased, consider
the following estimation procedure: To estimate the mean
of a population with the finite variance σ2, we first take
a random sample of size n. Then we randomly draw one
of n slips of paper numbered from 1 through n, and if the
number we draw is 2, 3, ..., or n, we use as our estimator
the mean of the random sample; otherwise, we use the
estimate n2. Show that this estimation procedure is
(a) consistent;
(b) neither unbiased nor asymptotically unbiased.
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