This was already clear from Rich Heiberger's reply. But my point was not
that the as.matrix() coercion was necessary, but that it would be wise, as
operations with matrices are generally (often much) more efficient than
with data frames. Of course, other considerations may exist, but that was
my
Hello,
The answer is given but there is no need to coerce to matrix first, as
long as the columns are numeric.
From ?exp, right at the beginning of section Details:
Details
All except logb are generic functions: methods can be defined for them
individually or via the Math group generic.
Thank you so much!
On Thu, Oct 14, 2021 at 12:17 PM Bert Gunter wrote:
> As all of your columns are numeric, you should probably convert your df to
> a matrix. Then use exp() on that, of course:
> exp(as.matrix(b))
>
> see ?exp
>
> Bert Gunter
>
> "The trouble with having an open mind is that
As all of your columns are numeric, you should probably convert your df to
a matrix. Then use exp() on that, of course:
exp(as.matrix(b))
see ?exp
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in
Hi All,
I have a data frame like this:
> head(b)
LRET02LRET04LRET06LRET08LRET10LRET12LRET14
1 0 0.6931472 . 1.0986123 1.0986123 1.0986123 0.6931472
2 2.1972246 2.4849066 2.4849066 . 2.5649494 2.6390573 2.6390573
3 1.6094379 1.7917595 1.6094379
5 matches
Mail list logo
