Geodesic
Dynamic credibility with outliers and missing observations
Applications of Mathematics, Tome 41 (1996) no. 2, pp. 149-159

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In actuarial practice the credibility models must face the problem of outliers and missing observations. If using the $M$-estimation principle from robust statistics in combination with Kalman filtering one obtains the solution of this problem that is acceptable in the numerical framework of the practical actuarial credibility. The credibility models are classified as static and dynamic in this paper and the shrinkage is used for the final ratemaking.
In actuarial practice the credibility models must face the problem of outliers and missing observations. If using the $M$-estimation principle from robust statistics in combination with Kalman filtering one obtains the solution of this problem that is acceptable in the numerical framework of the practical actuarial credibility. The credibility models are classified as static and dynamic in this paper and the shrinkage is used for the final ratemaking.
DOI : 10.21136/AM.1996.134318
Classification : 60G35, 62M20, 62P05, 93E11
Keywords: credibility; actuarial science; outliers; missing observations; robust Kalman filter; shrinkage; time series; risk 
Cipra, Tomáš. Dynamic credibility with outliers and missing observations. Applications of Mathematics, Tome 41 (1996) no. 2, pp. 149-159. doi: 10.21136/AM.1996.134318
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