Abstract
AbstractComputationally efficient evaluation of penalized estimators of multivariate exponential family distributions is sought. These distributions encompass among others Markov random fields with variates of mixed type (e.g., binary and continuous) as special case of interest. The model parameter is estimated by maximization of the pseudo-likelihood augmented with a convex penalty. The estimator is shown to be consistent. With a world of multi-core computers in mind, a computationally efficient parallel Newton–Raphson algorithm is presented for numerical evaluation of the estimator alongside conditions for its convergence. Parallelization comprises the division of the parameter vector into subvectors that are estimated simultaneously and subsequently aggregated to form an estimate of the original parameter. This approach may also enable efficient numerical evaluation of other high-dimensional estimators. The performance of the proposed estimator and algorithm are evaluated and compared in a simulation study. Finally, the presented methodology is applied to data of an integrative omics study.
Publisher
Springer Science and Business Media LLC
Subject
Computational Theory and Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability,Theoretical Computer Science
Reference21 articles.
1. Besag, J.: Spatial interaction and the statistical analysis of lattice systems. J. R. Stat. Soc. Ser. B Methodol. 36(2), 192–236 (1974)
2. Bilgrau, A.E., Peeters, C.F.W., Eriksen, P.S., Bøgsted, M., van Wieringen, W.N.: Targeted fused ridge estimation of inverse covariance matrices from multiple high-dimensional data classes. J. Mach. Learn. Res. 21(26), 1–52 (2020)
3. Boyle, E.A., Li, Y.I., Pritchard, J.K.: An expanded view of complex traits: from polygenic to omnigenic. Cell 169(7), 1177–1186 (2017)
4. Chen, S., Witten, D.M., Shojaie, A.: Selection and estimation for mixed graphical models. Biometrika 102(1), 47–64 (2015)
5. Das, A K., Netrapalli, P., Sanghavi, S., Vishwanath, S.: Learning Markov graphs up to edit distance. In Information Theory Proceedings (ISIT), 2012 IEEE International Symposium on, pages 2731–2735. IEEE, 2012
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