Depending on the definition of the inference task, the statistical risk can either be the estimation error, prediction error, or detection probability, for example.
12.
Let \ textbf { y }-\ hat { \ textbf { y } } denote the output estimation error exhibited by a conventional Kalman filter.
13.
One way of proceeding is to identify a system which generates the estimation error and setting \ textbf { W } equal to the inverse of that system.
14.
The raw figure obtained by the equation should be adjusted up or downwards, within the confidence limit suggested by the quoted estimation errors, and according to the following principles:
15.
Not accounting for these attributes lead to severe estimation error in the correlations and variances that have negative biases ( as much as 70 % of the true values ).
16.
Not accounting for these attributes lead to severe estimation error in the correlation and Variance Covariance that have negative biases ( as much as 70 % of the true values ).
17.
Not accounting for these attributes can lead to severe estimation error in the correlations and covariances that have negative biases ( as much as 70 % of the true values ).
18.
Not accounting for these attributes lead to severe estimation error in the correlations, variances and covariances that have negative biases ( as much as 70 % of the true values ).
19.
The addition of a flat trajectory makes it particularly popular in plains states where the open fields can require longer-range shots on game, as this flatness tends to minimize range-estimation errors by the hunter.
20.
These models correlate the data for different performance counters with power consumption and static models like above examples ( First-order and Piece-wise linear ) have different estimation errors due to variations across identical hardware.
