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# How to Derive Bias and Mean Square Error for an Estimator?

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- Hing Cheung So
- Last updated:
- 23 February 2016 - 1:43pm
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- Presentation Slides

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Analyzing the performance of estimators is a typical task in signal processing. Two fundamental performance measures in the aspect of accuracy are bias and mean square error (MSE). In this presentation, we revisit a simple technique to produce the bias and MSE of an estimator that minimizes or maximizes an unconstrained differentiable cost function over a continuous space of the parameter vector under the small error conditions. This presentation is a companion work of: H. C. So, Y. T. Chan, K. C. Ho and Y. Chen, "Simple formulas for bias and mean square error computation," IEEE Signal Processing Magazine, vol. 30, no. 4, pp. 162-165, July 2013.