Factor analysis is related to principal components where

linear combinations of the original variables are created, such that the first component has the most variation, the second component has the next most variation, etcetera.

preliminary transformation of a signal at a transmitting end by 'splitting' this signal into parts (strips) of equal duration (length), forming their

linear combinations and then 'sticking' them together into a single signal of the same (or greater) duration".

Zhang, Analysis of max-min eigenvalue of constrained

linear combinations of symmetric matrices, in Proceedings ofthe IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, 2007, pp.

5, which states that most such functions can be expanded as

linear combinations of dilates of Fejer functions [(sin[pi]n[gamma]/[pi]n[gamma]).

It follows from this equation that rows of the matrix [PHI]F are

linear combinations of the matrix [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] rows; this is equivalent to the rank equality

The specific

linear combinations tested are the residuals from a static cointegrating regression such as: [Y.

Some treatment combinations are constructed from the

linear combinations [A.

Figure 4 represents the lines of the

linear combinations and the experimental points.

The number of statistically significant

linear combinations indicates the number of demand series that are statistically distinct.

We undertook investigation of all three methods because it was not evident a priori which would be most successful in the discrimination after

linear combinations capturing the information contained in this complicated 8-variable data set were introduced as new simplifying variables.

Equations (18)-(20) represent three

linear combinations of the disturbances to the model that uninformed agents receive when the monetary authority follows a strict money rule.

The technique essentially transforms the original variables into a smaller set of

linear combinations that account for most of the variance of the original set.