Evaluating causal relationships in wireless sensor/actuator networks

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn V, Issue , 2005, Pages

  Coates, Mark ^a  

^a MCGILL UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ACTUATORS; COMPUTER NETWORKS; DISTRIBUTED COMPUTER SYSTEMS; LARGE SCALE SYSTEMS;

ACTUATOR NETWORKS; DISTRIBUTED TREATMENT STRATEGIES; WIRELESS SENSOR;

SENSORS;

EID: 33646810121     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2005.1416459     Document Type: Conference Paper

References (12)

1. K.A. Delin, R.P. Harvey, N.A. Chabot, S.P. Jackson, M. Adams, D.W. Johnson, and J.T. Britton, "Sensor web in Antarctica: developing an intelligent, autonomous platform for locating biological flourishes is cryogenic environments," in Proc. 34th Lunar and Planetary Science Conf., Houston, TX, Mar. 2003.
2. D. Myung, B. Duncan, D. Malan, M. Welsh, M. Gaynor, and S. Moulton, "Vital dust: Wireless sensors and a sensor network for real-time patient monitoring," in Proc. 8th New England Reg. Trauma Conf., Burl., MA, Nov. 2003.
3. J. Neyman, "On the application of probability theory to agricultural experiments, (originally appeared in Essay on prin ciples (section 9), 1923)," translated in Statistical Science, vol. 5, pp. 34-58, 1990.
4. D.B. Rubin, "Bayesian inference for causal effects: The role of randomization," The Annals of Statistics, vol. 6, pp. 34-58, 1978.
5. J.M. Robins, "A new approach to causal inference in mortality studies with a sustained exposure period: Application to control of the healthy worker survivor effect.," Mathematical Modelling, vol. 7, pp. 1393-1512, 1986.
6. J.M. Robins, Latent Variable Modelling and Applications to Causality, vol. 120 of Lecture Notes in Statistics, chapter Causal inference from complex longitudinal data, pp. 69-117, Springer-Verlag, New York, 1997.
7. S.A. Murphy, M.J. van der Laan, and J.M. Robins, "Marginal mean models for dynamic treatment regimes," J. American Statistical Association, vol. 96, no. 456, pp. 1410-1423, 2001.
8. S.A. Murphy, "Optimal dynamic treatment regimes," J. Roy. Stat. Soc., Series B, vol. 65, no. 2, pp. 331-366, 2003.
9. Y. Wang and M.J. van der Laan, "Data adaptive estimation of the treatment specific mean," Tech. Rep., U.C. Berkeley, Division of Biostatistics, 2004.
10. C. Scott, R. Willett, and R. Nowak, "Cort: Classification or regression trees," in P roc. IEEE ICASSP, Hong Kong, China, April 2003.
11. R. Castro, R. Willett, and R. Nowak, "Coarse-to-fine manifold learning," in P roc. IEEE ICASSP, Montreal, Canada, May 2004.
12. Mark Coates, "Estimation of the marginal mean response using wireless sensor-actuator networks," Tech. Rep., Department of Electrical and Computer Engineering, McGill University, 2005, available at http://www.tsp.ece.mcgill.ca/Networks/.