An equation was proposed to model the mean roughness in the studied experimental region.
In this model, the mean of the current claim number depends on the previous observations.
For this model, the mean square error compared to the theoretical power level is 2.5 dB.
For the crash model the mean shift is located at July 1978.
In Section 3, for the classical model, the mean (L_{p} -consistency is given, which generaL_{p} -consistencyorem [6].
To evaluate the performance of the model, the mean square error (MSE) and correlation coefficient (R2) in the test data were calculated.
In past studies using the CCI model and the crushed sciatic nerve model, the mean intensity decreased (Vrinten and Hamers 2003; Bozkurt et al. 2008).
In our Bayesian model, the mean of prior distribution for σ2 is close to 0.3, and the expectation of σ exceeds 0.215 for most sequences.
In this model, the mean path loss is modeled deterministically, whereas the shadow fading and small-scale fading are modeled statistically.
To quantify the association of the OSDI score with the risk factors, we model the mean of the Beta distribution as a regression function of these factors.
Since PESQ measurements principally model the Mean Opinion Scores (MOS), it has a close connection to subjective performance tests performed by a human.
