The phrase "average function as" is not correct in standard written English.
It may be intended to describe how something serves as an average, but the construction is awkward and unclear.
Example: "The average function as a measure of central tendency is crucial in statistics."
Alternatives: "serve as an average" or "act as an average.".
For example, gossip based aggregation (Jelasity et al. 2005) calculates the average function as an iterative variance reduction algorithm over the values of nodes in an overlay network.
Though this assumption does not hold in the DWT domain in which the histogram in Figure 3 is near the Gaussian distribution, the best result of state matching function model is the average function as demonstrated in Table 5.
You take interaural correlation functions from each frequency channel, normalize them, average them across channels (weighted or unweighted), then define the peak of this average function as the interaural correlation.
We present samples of average distribution functions, as well as average flux patterns based on the average distribution functions, all suitable for detailed comparison with models of the near-Mars space environment.
The raw data were background corrected, normalized, and summarized using Guanine-Cytosine Robust Multichip Average (GCRMA) function as described in [ 22].
Data normalization and background correction were performed using guanine-cytosine Robust Multichip Average (gcRMA) function as described in [ 54]. gcRMA adjusts for background intensities in Affymetrix array data which include optical noise and non-specific binding (NSB).
Weighted averaging functions, such as Ordered Weighted Averaging (OWA) or the weighted mean, can be quite convenient aggregation functions when we deal with data fusion tasks, in which criteria of interest are expressed with numerical values (usually, in [0,1] n ).
Then can be estimated as weighted average through kernel function, as follows: 5 and are estimates of p0 and p1, respectively.
To generate a smooth, genome-wide distribution of these statistics, a kernel smoothing average using a Gaussian function as described in Hohenlohe et al. (2010).
These authors used a control-group averaged input function (modeled as a sum of three exponentials) plus single venous sampling to fix the unknown amplitudes of the exponentials.
Random noise was added to genera average enzyme function counts as a multiple n of the standard deviation of enzyme function counts across all sequenced bacterial genomes.
