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I have a bunch of data which is assumed to be instances of a geometric random variable with outliers. How can I do a robust estimation of the parameter $p$ so that the effect of outliers is minimized?

As a part of the estimation process, I also need to know which are the outliers in the data.

I am looking for some solution using R, matlab or C/C++.

EDIT

Is any algorithm available which can be used for robust estimation of geometric random variable, though not readily available as a function in R or matlab ?

I have a bunch of data which is assumed to be instances of a geometric random variable with outliers. How can I do a robust estimation of the parameter $p$ so that the effect of outliers is minimized?

As a part of the estimation process, I also need to know which are the outliers in the data.

I am looking for some solution using R, matlab or C/C++.

EDIT 1

Is any algorithm available which can be used for robust estimation of geometric random variable, though not readily available as a function in R or matlab ?

EDIT 2

The maximum likelihood estimate of p of geometric random variable is the mean of the instance values. So if we do robust estimate of mean of the instance values, can we say that we are doing robust estimation of the underlying geometric random variable? If so, which method is most suitable for doing the robust mean estimation. (I am a newbie in statistics and R)

I have a bunch of data which is assumed to be instances of a geometric random variable with outliers. How can I do a robust estimation of the parameter $p$ so that the effect of outliers is minimized?

As a part of the estimation process, I also need to know which are the outliers in the data.

I am looking for some solution using R, matlab or C/C++.

I have a bunch of data which is assumed to be instances of a geometric random variable with outliers. How can I do a robust estimation of the parameter $p$ so that the effect of outliers is minimized?

As a part of the estimation process, I also need to know which are the outliers in the data.

I am looking for some solution using R, matlab or C/C++.

EDIT

Is any algorithm available which can be used for robust estimation of geometric random variable, though not readily available as a function in R or matlab ?

I have a bunch of data which is assumed to be instances of a geometric random variable with outliers. How can I do a robust estimation of the p value so that the effect of outliers is minimized.

As a part of the estimation process, I also need to know which are the outliers in the data.

I am looking for some solution using R, matlab or C/C++.

Thanks

I have a bunch of data which is assumed to be instances of a geometric random variable with outliers. How can I do a robust estimation of the parameter $p$ so that the effect of outliers is minimized?

As a part of the estimation process, I also need to know which are the outliers in the data.

I am looking for some solution using R, matlab or C/C++.