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Incomplete observation sets should be avoided, as these are more likely to contain vital signs that should lead to an alert and more likely to be associated with errors that cause an alert not to be generated.
Incomplete observation sets were more likely to contain observations which should have led to an alert than complete observation sets (15.1% vs 7.6%, p<0.001), but less likely to have an alerting score correctly calculated (38.8% vs 30.0%, p<0.001).
Kaplan EL, Meier P (1958) Nonparametric estimation from incomplete observation.
However, the observation duration for sensors in the incomplete observation regions is reduced by at least half.
In addition, the problem of implementing the MPC methodology and nonlinear Kalman filter with inaccurate or incomplete observation data and long measurement periods is addressed.
This arises from an incomplete observation of some of the stores and fluxes in the water cycle (in particular: precipitation, evaporation, soil moisture and groundwater), problems with the simulation of precipitation by global climate models and the wide diversity of global hydrological models currently in use.
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Our approach is deliberately conservative: we make no assumptions about the so-called incompleteness mechanism that associates complete with incomplete observations.
Using an example, we show that our rule appears to provide a solid basis for reliable updating with incomplete observations, when no strong assumptions about the incompleteness mechanism are justified.
67 Multiple imputation is now an established technique for analysing data sets where there are incomplete observations, 68 while Bayesian inference, 69 hidden Markov models 70 and partially observed Markov process 71 have been used to overcome deficiencies in data collection when fitting epidemiological models to routine data.
Kaplan, E. & Meier, P. Nonparametric estimation from incomplete observations.
Reconstructing Patterns of Information Diffusion from Incomplete Observations.
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