2008/07/16 by Xiao-Li Meng · 1 citation
Mathematics · #Advanced Statistical Methods and Models #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #math.ST #msc:62F15 #msc:62F99 #stat.TH
paper · pdf · doi:10.1214/07-aos0316b
published as Annals of Statistics 2008, Vol. 36, No. 4, 1542-1552 · Published in at http://dx.doi.org/10.1214/07-AOS0316B the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
openalex publication_date 2008/07/16 · arxiv created 2008/08/07 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
An insider's minor comments. Section 2.3 seems to be the reason that I am a discussant. There, it was first stated that the proposed LLA algorithm is an instance of the MM algorithm, as termed by Lange, Hunter and Yang Then it was shown, under certain conditions, that it is also an EM algorithm. My initial reaction was "hmmm, the authors' reading of Lange, Hunter and Yang [8] must have ceased before reaching its discussions," because a more general "MM = EM" result using the same Laplace transform technique was the base for a key inquiry of Meng [10], a discussion of Lange, Hunter and Yang Upon a more careful reading, I realized that the authors' construction, though mathematically equivalent to mine, gives a different interpretation to the constructed missing data/latent variable. This is rather interesting, especially if my initial reaction was correct.