Analyze data with the Statistics software R: Difference between revisions

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=== The underlying source code ===
=== The underlying source code ===
[[The JavaScript and PHP code of the client]]
[[The underlying JavaScript and PHP code]]


The R script can be [http://jsxgraph.uni-bayreuth.de/~alfred/jsxgraph/branches/0.70/examples/LokSkala.R downloaded here].
The R script can be [http://jsxgraph.uni-bayreuth.de/~alfred/jsxgraph/branches/0.70/examples/LokSkala.R downloaded here].

Revision as of 11:56, 11 December 2008

Normal Location and Scale

This litte application sends the y-coordinates of the points which are normal distributed (pseudo-)random numbers to the server.
There, location and scale of the sample are estimated using the Statistics software R.
The return values are plotted and displayed.

The computed estimates are:

  • mean, standard deviation: red (non-robust!)
  • median and MAD: black (most-robust!)
  • optimally robust radius-minimax estimator: green (cf. Rieder et al. (2008))

By changing the y-position of the four movable points you should recognize the instability (non-robustness) of mean and standard deviation in contrast to the robust estimates; e.g., move one of the four movable points to the top of the plot.

Online results:

Statistics:<br>

The underlying source code

The underlying JavaScript and PHP code

The R script can be downloaded here.

References

  • The Costs of not Knowing the Radius, Helmut Rieder, Matthias Kohl and Peter Ruckdeschel, Statistical Methods and Application 2008 Feb; 17(1): p.13-40; cf. also [1] for an extended version.
  • Robust Asymptotic Statistics, Helmut Rieder, Springer, 1994.
  • Numerical Contributions to the Asymptotic Theory of Robustness, Matthias Kohl, PhD-Thesis, University of Bayreuth, 2005; cf. also [2].

External links