Srikesh G Arunajadai

Summary

Affiliation: Columbia University
Country: USA

Publications

  1. doi request reprint A point process driven multiple change point model: a robust resistant approach
    Srikesh G Arunajadai
    Department of Biostatistics and Anesthesiology, Columbia University Medical Center, PH5 505, New York, NY 10032, USA
    Math Biosci 220:57-71. 2009
  2. pmc Step detection in single-molecule real time trajectories embedded in correlated noise
    Srikesh G Arunajadai
    Department of Biostatistics, Columbia University, New York, New York, United States of America
    PLoS ONE 8:e59279. 2013
  3. pmc RNA unwinding by NS3 helicase: a statistical approach
    Srikesh G Arunajadai
    Department of Biostatistics and Anesthesiology, Columbia University, New York, New York, USA
    PLoS ONE 4:e6937. 2009
  4. doi request reprint Quadratic System Identification: a statistical framework for the paired-pulse paradigm
    Srikesh G Arunajadai
    Department of Biostatistics and Anesthesiology, Columbia University Medical Center, PH5 505, New York, NY 10032, USA
    Math Biosci 224:10-23. 2010
  5. doi request reprint A nonlinear model for highly unbalanced repeated time-to-event data: Application to labor progression
    Srikesh G Arunajadai
    Department of Biostatistics, Columbia University, New York, NY 10025, USA
    Stat Med 29:2709-22. 2010

Collaborators

Detail Information

Publications5

  1. doi request reprint A point process driven multiple change point model: a robust resistant approach
    Srikesh G Arunajadai
    Department of Biostatistics and Anesthesiology, Columbia University Medical Center, PH5 505, New York, NY 10032, USA
    Math Biosci 220:57-71. 2009
    ..Both sequential and a posteriori change point models are considered. The relevant parameters of interest are estimated using a maximum likelihood approach. Simulations are performed to assess the performance of the methodology...
  2. pmc Step detection in single-molecule real time trajectories embedded in correlated noise
    Srikesh G Arunajadai
    Department of Biostatistics, Columbia University, New York, New York, United States of America
    PLoS ONE 8:e59279. 2013
    ..Because this method is automated, and directly works with high bandwidth data without pre-filtering or assumption of gaussian noise, it may be broadly useful for analysis of single-molecule real time trajectories...
  3. pmc RNA unwinding by NS3 helicase: a statistical approach
    Srikesh G Arunajadai
    Department of Biostatistics and Anesthesiology, Columbia University, New York, New York, USA
    PLoS ONE 4:e6937. 2009
    ..7 base pairs. An interesting finding pertains to the stepping velocity. Our analysis indicates that stepping velocity may be of two kinds- a low and a high velocity...
  4. doi request reprint Quadratic System Identification: a statistical framework for the paired-pulse paradigm
    Srikesh G Arunajadai
    Department of Biostatistics and Anesthesiology, Columbia University Medical Center, PH5 505, New York, NY 10032, USA
    Math Biosci 224:10-23. 2010
    ..Simulation studies are performed to assess the performance of the methodology and to study the conditions under which the methods are expected to perform well...
  5. doi request reprint A nonlinear model for highly unbalanced repeated time-to-event data: Application to labor progression
    Srikesh G Arunajadai
    Department of Biostatistics, Columbia University, New York, NY 10025, USA
    Stat Med 29:2709-22. 2010
    ..Simulations are performed to assess the methodology and conditions are suggested for predicting the time to an event...