Sentence examples for order predictors from inspiring English sources

All remaining peaks were then tested for detection performance of biological variance by fitting a linear model between the estimated abundance and first order predictors based on the experimental factors ripening stage, genotype, treatment and harvesting time.

Several convenient meta server tools exist that combine different secondary structure and order predictors with additional information sources to provide more accurate domain predictions and even associated automated primer design, for example ProteinCCD [21] and the SGC Domain Boundary Analyser [22].

An obvious attempt would be to raise variables to a power to allow non-linearity, but a recent study still reported overprediction under a utility value of around.6 for a model with significant second order predictors [ 24].

We therefore proceed using a 10th order predictor, which is first converted to 10 LSF coefficients.

We assume that K is chosen large enough so that the optimal K-th order predictor is close to the infinite memory predictor.

The application of a limiter to antidiffusive element contributions guarantees that the corrected solution remains bounded by the local maxima and minima of the low order predictor.

Equation (23) is applicable only at the sensor and it describes the "local" behavior of the first order predictor while the data employed to compute (hat {s}_{i}^{(R)}[!n]) is available at the sensor and also at the sink.

The coefficients of the optimal K-th order predictor for {x n } are given by ({mathbf a}={mathbf R}_{X}^{-1}{mathbf r}_{X}), where a=(a 1,…,a K ) T, (i,j) element of the K×K Toeplitz matrix R X is r X (|i−j|), and r X = [ r X (1),…,r X (K)] T [8].

The overall second-order temporal accuracy is preserved even with the use of lower-order predictors.

Three data compression methods are compared; two predictive methods, namely zero-order and first-order predictors and a piece-wise linear approximation method, followed by run-length and Huffman coding.

Furthermore, as Table 1 shows, we were able to consistently generate datasets with a complex gene-disease relationship that lack low-order predictors.