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There are two problems with this estimator though it is robust to I/Q mismatch.
One problem with this estimator is that if the variables are close to a random walk, lagged levels are weak instruments for first differences.
The bias associated with this estimator is derived here and combined with previously derived expressions for the estimator variance to give both Type-I and Type-II errors for the detector.
A coefficient of determination value of 0.96 achieved with this estimator in LOS justified the simple linear regression function as the model that relates distance estimates to RTT measurements in LOS.
Although the results for the coefficients (not reported here) were similar with this estimator, this model did not pass the Pesaran (2004) test, indicating that there is cross-sectional dependence in the data.
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Three previous studies used this estimator, with overdiagnosis estimates ranging between 1% and 30.5% (7, 19, 20 ).
[12] have recently described a method to estimate the serial interval and then used this estimate with the estimator proposed in [7] of the daily reproductive number and have applied their method to data from outbreaks of avian influenza in poultry farms in Europe.
Plant breeders routinely use this estimator with randomized complete block designs as an ad hoc approximation with incomplete block designs.
We evaluate this estimator with the codebook C tp, which is marked as "MLE EstCH TS2/5".
An advantage of this estimator with respect to the traditional ones (Luenberger like for instance) is that it only requires one information to estimate the junction temperature : the dissipator temperature (no measure of the input).
Using surrogate data, we were able to demonstrate that the expected bias using this estimator with our sample set size (80 trials) is limited to a few percent (see Materials and Methods and Supplementary Materials).
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CEO of Professional Science Editing for Scientists @ prosciediting.com