In the MMSES case, all the trajectories tend to reach a zero steady state error whereas the BJ code error is characterized by two different behaviors.
This error is characterized by the Signal to Noise Ratio (SNR) [27], which can be expressed by (2).
The location error is characterized by its cumulative distribution function (CDF): Some results are represented in Figure 2, where we can see that the linearized LS approaches give higher errors when compared with range-free techniques in this environment and also are much more sensitive to location attacks.
For epidemiologic studies to be evaluated and used appropriately in risk assessment, it is important that exposure measurement error is characterized and evaluated thoroughly with consideration of the magnitude and direction of any potential exposure misclassification bias (Bergen et al. 2013).
The error in each estimate (parameter) used in the model, as described by its standard error, was characterized using an appropriate probability distribution (Table 1), except costs that were assumed known in the context of the evaluation.
The distribution of the positional error was characterized using a cumulative frequency distribution and summary descriptive statistics.
Distributions of all air pollutant measures more closely approximate lognormal distributions than normal distributions ([ 19], see Additional file 1, Table S1); therefore, additive error was characterized and modeled on a log concentration basis so that simulations with error added to a base case time-series would also have lognormal distributions.
Using a mixed model for repeated measures, the different sources of variability, being inter-tomato variability, intra-tomato variability and measurement error were characterized being of great benefit to the researcher.
In [5] this error was characterized in the time domain; in contrast, we pursue here a frequency-domain approach, which is needed to separate each RDM-like channel and will lead to a somewhat simpler expression.
The precision error was characterized by CVrms which was 3.2%.
Likewise, the uncertainty pertaining to power forecast errors is characterized through scenario sets.
