Fitting Mixtures of Erlangs to Censored and Truncated Data Using the EM Algorithm
ASTIN Bulletin, 2015, 45(3), 729-758.
28 Pages Posted: 21 Jan 2014 Last revised: 17 May 2017
Date Written: January 24, 2014
We present a calibration procedure for fitting mixtures of Erlangs to censored and truncated data by iteratively using the EM algorithm. Mixtures of Erlangs form a very versatile, yet analytically tractable, class of distributions making them suitable for modeling purposes.
The effectiveness of the proposed algorithm is demonstrated on simulated data as well as real data sets.
Keywords: Mixture of Erlang distributions with a common scale parameter; Censoring; Truncation; Expectation-maximization algorithm; Maximum likelihood
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