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There are 6845777 results for: content related to: Appendix E: Expectation–Maximization Algorithm

  1. Dynamic data rectification using the expectation maximization algorithm

    AIChE Journal

    Volume 46, Issue 8, August 2000, Pages: 1556–1565, Ashish Singhal and Dale E. Seborg

    Version of Record online : 16 APR 2004, DOI: 10.1002/aic.690460808

  2. Operating condition diagnosis based on HMM with adaptive transition probabilities in presence of missing observations

    AIChE Journal

    Volume 61, Issue 2, February 2015, Pages: 477–493, Nima Sammaknejad, Biao Huang, Weili Xiong, Alireza Fatehi, Fangwei Xu and Aris Espejo

    Version of Record online : 5 NOV 2014, DOI: 10.1002/aic.14661

  3. Mixtures of multivariate power exponential distributions


    Volume 71, Issue 4, December 2015, Pages: 1081–1089, Utkarsh J. Dang, Ryan P. Browne and Paul D. McNicholas

    Version of Record online : 1 JUL 2015, DOI: 10.1111/biom.12351

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    A joint model for multistate disease processes and random informative observation times, with applications to electronic medical records data


    Volume 71, Issue 1, March 2015, Pages: 90–101, Jane M. Lange, Rebecca A. Hubbard, Lurdes Y. T. Inoue and Vladimir N. Minin

    Version of Record online : 15 OCT 2014, DOI: 10.1111/biom.12252

  5. Two-stage marker-stratified clinical trial design in the presence of biomarker misclassification

    Journal of the Royal Statistical Society: Series C (Applied Statistics)

    Volume 65, Issue 4, August 2016, Pages: 585–601, Yong Zang, J. Jack Lee and Ying Yuan

    Version of Record online : 1 MAR 2016, DOI: 10.1111/rssc.12140

  6. Performance analysis of cooperative multi-carrier relay-based UAV networks over generalized fading channels

    International Journal of Communication Systems

    Volume 24, Issue 8, August 2011, Pages: 1049–1064, Ibrahim Y. Abualhaol and Mustafa M. Matalgah

    Version of Record online : 13 JAN 2011, DOI: 10.1002/dac.1212

  7. Nonlinear process identification in the presence of multiple correlated hidden scheduling variables with missing data

    AIChE Journal

    Volume 61, Issue 10, October 2015, Pages: 3270–3287, Lei Chen, Shima Khatibisepehr, Biao Huang, Fei Liu and Yongsheng Ding

    Version of Record online : 1 JUN 2015, DOI: 10.1002/aic.14866

  8. A two-component nonlinear mixed effects model for longitudinal data, with application to gastric emptying studies

    Statistics in Medicine

    Volume 29, Issue 17, 30 July 2010, Pages: 1839–1856, Inyoung Kim, Noah D. Cohen, Allen Roussel and Naisyin Wang

    Version of Record online : 19 MAY 2010, DOI: 10.1002/sim.3956

  9. Sequential minimal optimization in convex clustering repetitions

    Statistical Analysis and Data Mining: The ASA Data Science Journal

    Volume 5, Issue 1, February 2012, Pages: 70–89, Rikiya Takahashi

    Version of Record online : 16 DEC 2011, DOI: 10.1002/sam.10146

  10. Multiple testing for neuroimaging via hidden Markov random field


    Volume 71, Issue 3, September 2015, Pages: 741–750, Hai Shu, Bin Nan and Robert Koeppe

    Version of Record online : 26 MAY 2015, DOI: 10.1111/biom.12329

  11. Fast and accurate X-ray fluorescence computed tomography imaging with the ordered-subsets expectation maximization algorithm

    Journal of Synchrotron Radiation

    Volume 19, Issue 2, March 2012, Pages: 210–215, Qun Yang, Biao Deng, Weiwei Lv, Fei Shen, Rongchang Chen, Yudan Wang, Guohao Du, Fuhua Yan, Tiqiao Xiao and Hongjie Xu

    DOI: 10.1107/S0909049511052253

  12. Analysis of interval-censored recurrent event processes subject to resolution

    Biometrical Journal

    Volume 57, Issue 5, September 2015, Pages: 725–742, Hua Shen and Richard J. Cook

    Version of Record online : 7 JUL 2015, DOI: 10.1002/bimj.201400162

  13. The Expectation–Maximization Algorithm

    Missing Data in Clinical Studies

    Geert Molenberghs, Michael G. Kenward, Pages: 93–104, 2007

    Published Online : 11 MAY 2007, DOI: 10.1002/9780470510445.ch8

  14. Computing Projections

    Graphical Models: Representations for Learning, Reasoning and Data Mining, Second Edition

    Christian Borgelt, Matthias Steinbrecher, Rudolf Kruse, Pages: 139–156, 2009

    Published Online : 4 AUG 2009, DOI: 10.1002/9780470749555.ch5

  15. Prerequisite Fundamentals

    Process Control System Fault Diagnosis: A Bayesian Approach: A Bayesian Approach

    Ruben Gonzalez, Fei Qi, Biao Huang, Pages: 19–61, 2016

    Published Online : 1 AUG 2016, DOI: 10.1002/9781118770603.ch2

  16. EM Algorithm

    Nonparametric Statistics with Applications to Science and Engineering

    Paul H. Kvam, Brani Vidakovic, Pages: 307–321, 2007

    Published Online : 22 JAN 2007, DOI: 10.1002/9780470168707.ch16

  17. The dynamic ‘expectation–conditional maximization either’ algorithm

    Journal of the Royal Statistical Society: Series B (Statistical Methodology)

    Volume 74, Issue 2, March 2012, Pages: 313–336, Yunxiao He and Chuanhai Liu

    Version of Record online : 5 JAN 2012, DOI: 10.1111/j.1467-9868.2011.01013.x

  18. Penalized regression for interval-censored times of disease progression: Selection of HLA markers in psoriatic arthritis


    Volume 71, Issue 3, September 2015, Pages: 782–791, Ying Wu and Richard J. Cook

    Version of Record online : 13 MAR 2015, DOI: 10.1111/biom.12302

  19. Interpretation of electron microscope autoradiographs: correction for cross-fire when membrane components are highly labelled

    Journal of Microscopy

    Volume 166, Issue 2, May 1992, Pages: 219–230, Gilles Hejblum, Jean-Yves Mary, Vincent Morice and Andre Aurengo

    Version of Record online : 2 AUG 2011, DOI: 10.1111/j.1365-2818.1992.tb01520.x

  20. Haplotype frequency estimation in patient populations: The effect of departures from Hardy-Weinberg proportions and collapsing over a locus in the HLA region

    Genetic Epidemiology

    Volume 22, Issue 2, February 2002, Pages: 186–195, Richard M. Single, Diogo Meyer, Jill A. Hollenbach, Mark P. Nelson, Janelle A. Noble, Henry A. Erlich and Glenys Thomson

    Version of Record online : 10 JAN 2002, DOI: 10.1002/gepi.0163