Model order estimation is especially difficult for ill-conditioned systems.
Herein, the order estimation is embedded into the coarse motion estimation.
However, due to the very short length of the miRNA sequences, the results of order estimation were too poor.
Only order estimations were given in their papers.
Recently, a pitch estimation filter with amplitude compression (PEFAC) in the spectral domain has been proposed in [17], and methods for joint pitch and model order estimation have been proposed in [18] [20].
When a model failed to converge, first order PQL estimation was used, which yields slightly less accurate confidence intervals.
Because IMP retained acceptable numerical stability until final model development, first order conditional estimation was not retested for stability.
This implies that the minimum condition number GES for second-order tensor estimation is not an optimal GES for fourth-order tensor estimation.
Although high-order terms might not be negligible in this expansion, the contributions of low-order correlations to visual motion estimation are set by low-order terms.
Although this is largely ignored by other identification methods, system order estimation should be an integral part of a system identification algorithm.
