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5.7.4. An estimator ◊ is said to be squared-error consis- tent for 0 if lim E[(ên – 0)²] = 0. n→∞ - (a) Show that any squared-error consistent ê, is asymp- totically unbiased (see Question 5.4.15). (b) Show that any squared-error consistent Ôn is consis- tent in the sense of Definition 5.7.1.

5.7.4. An estimator ◊ is said to be squared-error consis- tent for 0 if lim E[(ên – 0)²] = 0. n→∞ - (a) Show that any squared-error consistent ê, is asymp- totically unbiased (see Question 5.4.15). (b) Show that any squared-error consistent Ôn is consis- tent in the sense of Definition 5.7.1.

MATLAB: An Introduction with Applications
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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5.7.4. An estimator ◊ is said to be squared-error consis- tent for 0 if lim E[(ên – 0)²] = 0. n→∞ - (a) Show that any squared-error consistent ê, is asymp- totically unbiased (see Question 5.4.15). (b) Show that any squared-error consistent Ôn is consis- tent in the sense of Definition 5.7.1.
Transcribed Image Text:5.7.4. An estimator ◊ is said to be squared-error consis- tent for 0 if lim E[(ên – 0)²] = 0. n→∞ - (a) Show that any squared-error consistent ê, is asymp- totically unbiased (see Question 5.4.15). (b) Show that any squared-error consistent Ôn is consis- tent in the sense of Definition 5.7.1.
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