[R] linear regression on groups of consecutive rows of a matrix

[Jim Bouldin]

I want to perform linear regression on groups of consecutive rows--say 5 to
10 such--of two matrices.  There are many such potential groups because the
matrices have thousands of rows. The matrices are both of the form:

> shp[1:5,16:20]
      SL495B SL004C SL005C SL005A SL017A
-2649   1.06   0.56     NA     NA     NA
-2648   0.97   0.57     NA     NA     NA
-2647   0.46   0.30     NA     NA     NA
-2646   0.92   0.48     NA     NA     NA
-2645   0.82   0.48     NA     NA     NA

That is, they both have NA values, and non-NA values, in the same matrix
positions.  In my attempts so far, I have had two problems.  First, in
using the split function (which I assume is essential here), I am unable to
split the matrices by groups of rows (say rows 1 to 5, 6 to 10, etc):

> shp_split = split(shp,row(shp))

will split the matrix by rows but not by groups thereof. Stumped.

Second, I cannot seem to get rid of the NA values, which would prevent the
regression even is I could figure out how to split the matrices correctly,
e.g.:
> shp_split = split(shp,row(shp))
> shp_split = shp_split[!is.na(shp_split)]
> shp_split[1]
$`1`
  [1] 0.68 0.28 0.43 0.47 0.64 0.40 0.69 0.56 0.62 0.40 1.01 0.67 0.17 1.36
1.84 1.06 0.56   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA
  NA   NA   NA etc

IF I solve these problems, will I in fact be able to perform individual
linear regressions on the (numerous) collections of 5 to 10 rows?

Thanks as always for any insight.


Jim Bouldin
Research Ecologist
Department of Plant Sciences, UC Davis
Davis CA, 95616
530-554-1740