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Theory and Methods

Hidden Markov Models With Applications in Cell Adhesion Experiments

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Pages 1469-1479 | Received 01 Dec 2011, Published online: 19 Dec 2013

REFERENCES

  • Akaike , H. 1974 . A New Look at the Statistical Model Identification . IEEE Transactions on Automatic Control , 19 : 716 – 723 .
  • Albert , P. S. , McFarland , H. F. , Smith , M. E. and Frank , J. A. 1994 . Time Series for Modeling Counts From a Relapsing–Remitting Disease: Application to Modeling Disease Activity in Multiple Sclerosis . Statistics in Medicine , 13 : 453 – 466 .
  • Altman , R. M. 2004 . Assessing the Goodness of Fit of Hidden Markov Models . Biometrics , 60 : 444 – 450 .
  • Baum , L. E. , Petrie , T. , Soules , G. and Weiss , N. 1970 . A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains . The Annals of Mathematical Statistics , 41 : 164 – 171 .
  • Bhattacharya , P. K. 1994 . Some Aspects of Change-Point Analysis . IMS Lecture Notes: Monograph Series , 23 : 28 – 56 .
  • Bickel , P. J. , Ritov , Y. and Rydén , T. 1998 . Asymptotic Normality of the Maximum-Likelihood Estimator for General Hidden Markov Models . The Annals of Statistics , 26 : 1614 – 1635 .
  • Cappe , O. , Moulines , E. and Rydén , T. 2005 . Inference in Hidden Markov Models , New York : Springer .
  • Celeux , G. and Durand , J. 2008 . Selecting Hidden Markov Model State Number With Cross-Validated Likelihood . Computational Statistics , 23 : 541 – 564 .
  • Chambaz , A. , Garivier , A. and Gassiat , E. 2009 . A Minimum Description Length Approach to Hidden Markov Models With Poisson and Gaussian Emissions. Application to Order Identification . Journal of Statistical Planning and Inference , 139 : 962 – 977 .
  • Chen , J. and Kalbfleisch , J. D. 1996 . Penalized Minimum-Distance Estimates in Finite Mixture Models . The Canadian Journal of Statistics , 24 : 167 – 175 .
  • Chen , J. and Khalili , A. 2008 . Order Selection in Finite Mixture Models . Journal of the American Statistical Association , 103 : 1674 – 1683 .
  • Chen , W. , Evans , A. E. , McEver , R. P. and Zhu , C. 2008 . Monitoring Receptor–Ligand Interactions Between Surfaces by Thermal Fluctuations . Biophysical Journal , 94 : 694 – 701 .
  • Clairambault , J. , Curzi-Dascalova , L. , Kauffmann , F. , Médigue , C. and Leffler , C. 1992 . Heart Rate Variability in Normal Sleeping Full-Term and Preterm Neonates . Early Human Development , 28 : 169 – 183 .
  • Csiszár , I. and Shields , P. 2000 . The Consistency of the BIC Markov Order Estimator . The Annals of Statistics , 28 : 1601 – 1619 .
  • Dempster , A. P. , Laird , N. M. and Rubin , D. B. 1977 . Maximum Likelihood From Incomplete Data via the EM Algorithm . Journal of the Royal Statistical Society, Series B , 39 : 1 – 38 .
  • Donoho , D. and Johnstone , I. 1994 . Ideal Spatial Adaption by Wavelet Shrinkage . Biometrika , 81 : 425 – 455 .
  • Dustin , M. L. , Bromley , S. K. , Davis , M. M. and Zhu , C. 2001 . Identification of Self through Two-Dimensional Chemistry and Synapses . Annual Review of Cell and Developmental Biology , 17 : 133 – 157 .
  • Fan , J. and Li , R. 2001 . Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties . Journal of the American Statistical Association , 96 : 1348 – 1360 .
  • Gassiat , E. and Boucheron , S. 2003 . Optimal Error Exponents in Hidden Markov Models Order Estimation . IEEE Transactions on Information Theory , 49 : 964 – 980 .
  • Gassiat , E. and Kéribin , C. 2000 . The Likelihood Ratio Test for the Number of Components in a Mixture With Markov Regime . ESAIM Probability and Statistics , 4 : 25 – 42 .
  • Giudici , P. , Rydén , T. and Vandekerkhove , P. 2000 . Likelihood-Ratio Tests for Hidden Markov Models . Biometrics , 56 : 742 – 747 .
  • Hawkins , D. M. and Zamba , K. D. 2005 . A Change Point Model for Shift in Variance . Journal of Quality Technology , 37 : 21 – 31 .
  • Hughes , J. P. and Guttorp , P. 1994 . A Class of Stochastic Models for Relating Synoptic Atmospheric Patterns to Regional Hydrologic Phenomena . Water Resources Research , 30 : 1535 – 1546 .
  • Hung , Y. , Zarnitsyna , V. , Zhang , Y. , Zhu , C. and Wu , C. F. J. 2008 . Binary Time Series Modeling With Application to Adhesion Frequency Experiments . Journal of the American Statistical Association , 103 : 1248 – 1259 .
  • Hunter , D. and Li , R. 2005 . Variable Selection Using MM algorithms . The Annals of Statistics , 33 : 1617 – 1642 .
  • Kaleh , G. K. and Vallet , R. 1994 . Joint Parameter Estimation and Symbol Detection for Linear or Nonlinear Unknown Channels . IEEE Transactions on Communications , 42 : 2406 – 2413 .
  • Koski , T. 2001 . Hidden Markov Models for Bioinformatics , New York : Springer .
  • Krishnaiah , P. R. and Miao , B. Q. 1988 . “ Review about Estimation of Change Points ” . In Handbook of Statistics (7 ed.) , Edited by: Krishnaiah , P. R. and Rao , C. R. New York : Elsevier .
  • Leroux , B. G. 1992 . Maximum-Likelihood Estimation for Hidden Markov Models . Stochastic Processes and Their Applications , 40 : 127 – 143 .
  • Leroux , B. G. and Puterman , M. L. 1992 . Maximum-Penalized Likelihood Estimation for Independent and Markov-Dependent Mixture Models . Biometrics , 48 : 545 – 558 .
  • MacDonald , I. and Zucchini , W. 1997 . Hidden-Markov and Other Models for Discrete-Valued Time Series , New York : Chapman & Hall .
  • MacKay , R. J. 2002 . Estimating the Order of a Hidden Markov Model . The Canadian Journal of Statistics , 30 : 573 – 589 .
  • Marshall , B. T. , Sarangapani , K. K. , Wu , J. , Lawrence , M. , McEver , R. P. and Zhu , C. 2006 . Measuring Molecular Elasticity by Atomic Force Microscope Cantilever Fluctuations . Biophysical Journal , 90 : 681 – 692 .
  • Meng , X. L. and Rubin , D. B. 1993 . Maximum Likelihood Estimation via the ECM Algorithm: A General Framework . Biometrika , 80 : 267 – 278 .
  • Rabiner , L. 1989 . A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition . Proceedings of the IEEE , 77 : 257 – 286 .
  • Rahul , M. , Friedman , J. H. and Hastie , T. 2011 . SparseNet: Coordinate Descent With Nonconvex Penalties . Journal of the American Statistical Association , 106 : 1125 – 1138 .
  • Robert , C. P. , Rydén , T. and Titterington , D. M. 2000 . Bayesian Inference in Hidden Markov Models Through the Reversible Jump Markov Chain Monte Carlo Method . Journal of the Royal Statistical Society, Series B , 62 : 57 – 75 .
  • Scott , S. L. , James , G. M. and Sugar , C. A. 2005 . Hidden Markov Models for Longitudinal Comparisons . Journal of the American Statistical Association , 100 : 359 – 369 .
  • Schwarz , G. E. 1978 . Estimating the Dimension of a Model . The Annals of Mathematical Statistics , 6 : 461 – 464 .
  • Stone , M. 1974 . Cross-Validatory Choice and the Assessment of Statistical Predictions . Journal of the Royal Statistical Society, Series B , 36 : 111 – 133 .
  • Tibshirani , R. 1996 . Regression Shrinkage and Selection via the Lasso . Journal of the Royal Statistical Society, Series B , 58 : 267 – 288 .
  • Tibshirani , R. J. 1997 . The Lasso Method for Variable Selection in the Cox Model . Statistics in Medicine , 16 : 385 – 395 .
  • Wang , P. and Puterman , M. L. 1999 . Markov Poisson Regression Models for Discrete Time Series . Journal of Applied Statistics , 26 : 855 – 869 .
  • Wu , C. F. J. 1983 . On the Convergence Properties of the EM algorithm . The Annals of Statistics , 11 : 95 – 103 .
  • Wu , J. H. , Fang , Y. , Yang , D. and Zhu , C. 2005 . Thermo-Mechanical Responses of a Surface-Coupled AFM Cantilever . Journal of Biomechanical Engineering , 127 : 1208 – 1215 .
  • Yuan , M. and Kendziorski , C. 2006 . Hidden Markov Models for Microarray Time Course Data in Multiple Biological Conditions . Journal of the American Statistical Association , 101 : 1323 – 1340 .
  • Zarnitsyna , V. I. , Huang , J. , Zhang , F. , Chien , Y. , Leckband , D. and Zhu , C. 2007 . Memory in Receptor-Ligand-Mediated Cell Adhesion . Proceedings of the National Academy of Sciences , 104 : 18037 – 18042 .
  • Zou , H. and Hastie , T. 2005 . Regularization and Variable Selection via the Elastic Net . Journal of Royal Statistical Society, Series B , 67 : 301 – 320 .
  • Zou , H. 2006 . The Adaptive Lasso and its Oracle Properties . Journal of the American Statistical Association , 101 : 1418 – 1429 .
  • Zou , H. and Li , R. 2008 . One-Step Sparse Estimates in Nonconcave Penalized Likelihood Models . The Annals of Statistics , 36 : 1509 – 1533 .

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