Hello fellow R-users,
Iâve been mulling this problem over for some time now and have decided it is
something I have to deal with but canât, so here goes:
I have a dataset (called maindata, it is 271 columns *13890 rows so I wont post
the entire thing here, Iâll just explain the situation!)
I am trying to calculate inter-environment correlation (rF = cov A,B /
sq.root(varA * varB ) for each row of the dataset. the values needed are (in 80
of the columns 2*40) in columns 174-213, and 214-253 respectively which
represent two environments (A or B).
Each of those columns is labelled with Xnumber.A/B
e.g. X208.A is column 174 (which also relates to the first column in the B
environment groups, col.214, X208.B)
effectively the equation is:
rF= cov (columns[174:213] , [214:253]) / sqrt( (var[174:213]) *
(var[214:253]) )
I want each of the 13890 rows to then have the rF value at the end of it (which
will then be used later against other variables)
Can anyone help me with this problem? Iâve tried allsorts and I have run out
of ideas.
Thanks in advance,
Rob
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
