M

#### Marston

Each of these columns of data are candidates for a multiple variable

regression.

One column represents the dependent data, the other columns the

independent data.

Over time which columns of data in collection create the best

regression varies in time.

My definition of best columns for the regression is that for each

column of data:

abs(Index(linest(Ax:Ay, non-contigous columns,0,true),n,1)/

Index(linest(Ax:Ay,non-contigous columns,0,true),n,2))>2

Index(linest(Ax:Ay,non-contigous columns,0,true),1,3) >

Index(linest(Ax:Ay, non-contigous columns (less 1),0,true),1,3) >0

There's a little I'm leaving out like the fact that linest orders the

results in the array backwards from the order the columns are ordered

from the second range of values - but I know how to handle this. Also

the second condition is a bit of a simplification - but again, that

something I understand.

What I don't know is how to get around the issue that linest requires

that columns be contiguous in order to conduct its analysis.

Is there any function that could do something like new array =

(A1:A100, C1100, Z1:Z100) and it lines up the columns as if

A,C,D,and Z were contigous?

Thanks in advance

Marston