For example, the errors are classified into four in [11]: (a) odometry error, (b) sensor noise, (c) error between the model environment and the real working environment, and (d) alteration of the environment, such as appearance of a new object.
For example, NoSuchBucket errors are caused by the customer when they try to upload a file into a non-existent bucket; whereas an InternalError code indicates that S3 is experiencing internal problems.
While it is possible to take negative time steps in the case of hyperbolic equations, in parabolic problems this almost certainly leads to numerical instabilities as, for example, roundoff errors are exponentially amplified in each backward step.
Last, the formula for the linear buckling load is verified by numerical examples, the errors are analyzed, and a corresponding correction factor is provided.
The examples of errors are shown in Additional file 4: Figure S3 (B).
Examples of errors are faulty algorithms for dose calculation; wrong default dosing or route; user-interface facilitated errors; fragmentation errors due to faulty integration between applications; programming errors; as well as "false expectations" of clinicians who rely too whole-heartedly on the system's capabilities [ 13, 17, 19- 21].
For example, if the errors are systematically biased towards one direction (for example latitudinally as in the case of geolocation data), it would be straightforward to determine another metric based on the output from the random walks.
In Example 6, the maximum absolute errors has been calculated at large time levels (t=5,10,15,20), and in Example 9, the errors are computed at (t=4).
In the demonstrative example, radar measurement errors are served as specifications while characterizing the acquirable zone of the ground-based radar system.
We also compare the finite sample behavior of the two estimators through a numerical example when the errors are long-memory.
