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Reviewing by Shaobo Fang (to be continued): | Reviewing by Shaobo Fang (to be continued): | ||
| − | + | The mathmatical derivation is clear and thorough, and hence very impressive. | |
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Summary:The author investigated briefly over the expected value of MLE estimate based on standard deviation and expected deviation. The case of maximum likelihood estimation examples for Gaussian R.V. both mu and sigma unknown was investigated and is truely interesting since in real world even if the data come in with Gaussian distribution the parameter is probably still unknown. Biasness of an estimator was also briefly investigaed at the very end. | Summary:The author investigated briefly over the expected value of MLE estimate based on standard deviation and expected deviation. The case of maximum likelihood estimation examples for Gaussian R.V. both mu and sigma unknown was investigated and is truely interesting since in real world even if the data come in with Gaussian distribution the parameter is probably still unknown. Biasness of an estimator was also briefly investigaed at the very end. | ||
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Could have been improved: It would be better for the reader if more context would be there to provide better transition regarding different parts. | Could have been improved: It would be better for the reader if more context would be there to provide better transition regarding different parts. | ||
Revision as of 16:41, 12 May 2014
Questions and Comments for: Expected Value of MLE estimate over standard deviation and expected deviation
A slecture by Zhenpeng Zhao
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Questions and Comments
Reviewing by Shaobo Fang (to be continued):
The mathmatical derivation is clear and thorough, and hence very impressive.
Summary:The author investigated briefly over the expected value of MLE estimate based on standard deviation and expected deviation. The case of maximum likelihood estimation examples for Gaussian R.V. both mu and sigma unknown was investigated and is truely interesting since in real world even if the data come in with Gaussian distribution the parameter is probably still unknown. Biasness of an estimator was also briefly investigaed at the very end.
Could have been improved: It would be better for the reader if more context would be there to provide better transition regarding different parts.
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