Therefore, the intention of the study was to validate the application of a simple linear regression as an alignment procedure.
As the p-value depends on the length of the alignment, we have used the linear regression (−0.2837' · length of alignment + 66.0155)/100 to adjust it to different satellite lengths.
These methods included multiple linear regression [ 15], multiple sequence alignment [ 16], energy optimization [ 17], support vector regression [ 18, 19], neural network [ 20, 21], pace regression [ 22], agent-based system [ 23] and k-nearest neighbor (KNN) [ 24].
In particular, the authors model the optical alignment score under the null hypothesis that the alignment is spurious using multiple linear regression on the number of query map fragments N, the map length L, and their product NL.
At each alignment position, the entropy of these subset alignments of size N was plotted against 1/N, using a linear regression to extrapolate the entropy estimate for N→∞.
Multiple linear regression models were developed to estimate the effects of the combined alignments on lateral acceleration.
Results: Forward-stepwise multiple linear regression indicated that the extent of degenerative changes could be best predicted from a linear combination of the independent variables, varus alignment, and standing balance (R =.80, F2,17 = 14.81, p =.0002).
The line actually represents a statistical calculation known as linear regression and a more accurrate description is provided above.
