I would really appreciate it if someone can give suggestions on how to
do spectra fitting in R using ordinary least square fitting and
non-negativity constraints. The lm() function works well for ordinary
least square fitting, but how to specify non-negativity constraints? It
wouldn't make sense
Xu, Xiuli (NIH/NHLBI) [E] wrote:
I would really appreciate it if someone can give suggestions on how to
do spectra fitting in R using ordinary least square fitting and
non-negativity constraints. The lm() function works well for ordinary
least square fitting, but how to specify non-negativity
On Fri, 14 Jul 2006, Joerg van den Hoff wrote:
Xu, Xiuli (NIH/NHLBI) [E] wrote:
I would really appreciate it if someone can give suggestions on how to
do spectra fitting in R using ordinary least square fitting and
non-negativity constraints. The lm() function works well for ordinary
Were you doing blind deconvolution or the spectrum basis are assummed to be
known?
As for blind deconvolution, alternatively you might consider alternating
least square, non-negative matrix factorization, or independent component
analysis + alternating least square as the post-processing.
yfl
