In Example 12.4.1, in contrast to Example 10.2.1, when we introduced the contaminated distribution for εi, we did not introduce a bias. Show that if we had, it would not have mattered. That is, if we assume then: (a) The least squares estimator b would still be an unbiased estimator of β. (b) The least squares estimator a has expectation
In Example 12.4.1, in contrast to Example 10.2.1, when we introduced the contaminated distribution for εi, we did not introduce a bias. Show that if we had, it would not have mattered. That is, if we assume
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The word "distribution" has several meanings in the financial world, most of them pertaining to the payment of assets from a fund, account, or individual security to an investor or beneficiary. Retirement account distributions are among the most...
then:
(a) The least squares estimator b would still be an unbiased estimator of β.
(b) The least squares estimator a has expectation α + δμ, so the model may just as well be assumed to be Yi = α + δμ + βxi + εi.
The word "distribution" has several meanings in the financial world, most of them pertaining to the payment of assets from a fund, account, or individual security to an investor or beneficiary. Retirement account distributions are among the most...
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