Under some practical situations, the MLSM suffers certain undesirable "breakage cells" problem.
What is remaining to investigate is the way to determine numbers of unknown parameters and their range of search under various practical situations where no or not plenty of a priori information exist.
Under many practical situations, it is difficult to obtain exact assessment values of the risk factors due to inherent vagueness and uncertainty in human judgments (Liu et al. 2014).
Therefore, the carbon isotope fractionations of LMWHs during evaporation from a mixture and from soil were investigated to explore their evaporation behavior under conditions resembling practical situations.
Asymptotic relative efficiency computation and simulation studies indicate that the proposed weighting estimators are more efficient than the inverse probability weighting estimators under wide range of practical situations especially when the missingness proportion is large.
To investigate the performance under the practical situation, we also consider the case when there exists a channel estimation error.
Another important motivation behind the ML-based approach lies in its asymptotic optimality, as observed in many practical situations of interest, under conditions of high SNR or long observation time [37].
The results show that the proposed inverse model is of interest in many practical situations and can be used under diverse conditions.
Since in practical situations, n > m, Eq. (2) is under determined.
