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Wu [8] investigated the weak and strong Bahadur representations of the M-estimates for linear models with stationary causal errors.
Several kinds of causal errors are considered under the broad heading, non causa pro causa and they are illustrated with reference to scientific explanations that have assigned false causes for empirical phenomena.
Starting from the assumption that the errors made by referees are impartial, it can be shown (Groot 2008) that stronger rather than weaker teams would benefit most if these causal errors were not made, and this would load the competitive imbalance.
In this way, we will compute the headroom for reductions in adverse event rates related to certain specific errors, i.e. the reduction in adverse event rates that would be expected if the causal errors could be eliminated.
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They may be removed, either by eliminating the causal error force or by negating it.
Although fidelity is increased, non-local activity spread results in the constant production of causal inference errors.
This eliminates causal inference errors that are made due to non-local correlations, and allows larger networks to be copied.
When stimulating one neuron in layer 0, activity can spread over a wide range of L0 and L1, and this allows the four types of causal inference error previously described, i.e. mistaken dependence, transitive inference, reciprocal interference and causal dominance.
Hence, the error on y5 in Figure 2 would be the sum or accumulation of the causal features labeled error-B, error-C, and error-5 in Figure 3.
Causal inferential memory errors were most pronounced among 5- and 6-year-olds.
The results showed that FHIA is a useful technique to better and more consistently identify the potential sources of human errors, causal factors in faults, multiple or common cause failures and correlation of cause-consequence of hazards during the various steps of the process.
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