Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix

2011-08-26 Thread josef . pktd
On Fri, Aug 26, 2011 at 2:57 PM, Charles R Harris wrote: > > > On Fri, Aug 26, 2011 at 12:38 PM, Mark Janikas wrote: >> >> Charles!  That looks like it could be a winner!  It looks like you always >> choose the last column of the U matrix and ID the columns that have the same >> values?  It works

Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix

2011-08-26 Thread Charles R Harris
On Fri, Aug 26, 2011 at 12:38 PM, Mark Janikas wrote: > Charles! That looks like it could be a winner! It looks like you always > choose the last column of the U matrix and ID the columns that have the same > values? It works when I add extra columns as well! BTW, sorry for my lack > of knowl

Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix

2011-08-26 Thread Mark Janikas
cussion-boun...@scipy.org<mailto:numpy-discussion-boun...@scipy.org>] On Behalf Of Mark Janikas Sent: Friday, August 26, 2011 10:35 AM To: Discussion of Numerical Python Subject: Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix I actually use the VIF when the design matrix can be

Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix

2011-08-26 Thread josef . pktd
t 26, 2011 10:35 AM > To: Discussion of Numerical Python > Subject: Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix > > I actually use the VIF when the design matrix can be inverted I do it the > quick and dirty way as opposed to the step regression: > > 1. Calc

Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix

2011-08-26 Thread Charles R Harris
t 26, 2011 10:35 AM > To: Discussion of Numerical Python > Subject: Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix > > I actually use the VIF when the design matrix can be inverted I do it > the quick and dirty way as opposed to the step regression: > > 1. Calc

Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix

2011-08-26 Thread Fernando Perez
On Fri, Aug 26, 2011 at 7:41 PM, Mark Janikas wrote: > I wonder if my last statement is essentially the only answer... which I > wanted to avoid... > > Should I just use combinations of the columns and try and construct the > corrcoef() (then ID whether NaNs are present), or use the condition nu

Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix

2011-08-26 Thread Mark Janikas
Sent: Friday, August 26, 2011 10:28 AM To: Discussion of Numerical Python Subject: Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix On Fri, Aug 26, 2011 at 1:10 PM, Mark Janikas wrote: > Hello All, > > > > I am trying to identify columns of a matrix that are perfectl

Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix

2011-08-26 Thread Mark Janikas
riday, August 26, 2011 10:28 AM To: Discussion of Numerical Python Subject: Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix On Fri, Aug 26, 2011 at 1:10 PM, Mark Janikas wrote: > Hello All, > > > > I am trying to identify columns of a matrix that are perfectly colline

Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix

2011-08-26 Thread Skipper Seabold
On Fri, Aug 26, 2011 at 1:10 PM, Mark Janikas wrote: > Hello All, > > > > I am trying to identify columns of a matrix that are perfectly collinear. > It is not that difficult to identify when two columns are identical are have > zero variance, but I do not know how to ID when the culprit is of a h

Re: [Numpy-discussion] Identifying Colinear Columns of a Matrix

2011-08-26 Thread Mark Janikas
ython' Subject: [Numpy-discussion] Identifying Colinear Columns of a Matrix Hello All, I am trying to identify columns of a matrix that are perfectly collinear. It is not that difficult to identify when two columns are identical are have zero variance, but I do not know how to ID when the culpr

[Numpy-discussion] Identifying Colinear Columns of a Matrix

2011-08-26 Thread Mark Janikas
Hello All, I am trying to identify columns of a matrix that are perfectly collinear. It is not that difficult to identify when two columns are identical are have zero variance, but I do not know how to ID when the culprit is of a higher order. i.e. columns 1 + 2 + 3 = column 4. NUM.corrcoef(m