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In [80], convergence of the error covariance has been analyzed for a rather general class of packet dropping models and alternative performance measures are introduced when the expectation of error covariance cannot be well defined.
We do suggest however, that until controlled two-source experiments are conducted, our single-source experiments provide some expectation of error for these methods.
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The MBQUNE is defined when and, as (29) Based on normally distributed observations with zero expectation of errors, this holds also for γ i, yielding (Eshagh and Sjöberg, 2008): (30).
Doing so is important to both the general public trying to understand polls and to pollsters themselves: If we're providing realistic expectations of error, polling "misses" that are actually reasonable based on expected survey error might be better understood.
We have firstly derived the analytical S-curve, defined as the conditional expectation of the error signal that controls the loop, and we have deduced an approximation of the asymptotic estimation error variance of the FD estimation algorithm.
The expectation of quantization error incurred by the RVQ is upper bounded by.
Using Lemma 4, we see that the steady state of expectation of the error vector is (36).
Lemma 4. For the SO-DCTS algorithm in (28), the expectation of the error vector is given by (32).
such that the expectation of an error near the end of the decision sequence is much higher.
A genotyping error of 0.00001 corresponds to an expectation of one genotyping error in approximately 100 kb of the target region.
Rather than trying to find the best channel estimator, we derive a timing metric that minimizes the expectation of the transmission error probability over all channel estimation errors.
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