On 06/10/2017 4:28 PM, David Hugh-Jones wrote:
Many measurements have no unit, but some uncertainty - e.g. the b and se
from an arbitrary regression. Can you give specific examples of the
advantages from binding these packages tightly together?
Just to nitpick: in the regression y = a + b x, b
Hi Iñaki and David,
I fully see the need in a standardized unit package, and I understand the need
for propagation of errors (though I'm in the opposite camp to David where I
usually need unit tracking and conversion and rarely need error propagation--
though that's because my error propagation
Many measurements have no unit, but some uncertainty - e.g. the b and se
from an arbitrary regression. Can you give specific examples of the
advantages from binding these packages tightly together?
On Fri, 6 Oct 2017 at 21:23, Iñaki Úcar wrote:
> El 6 oct. 2017 19:13, "David Hugh-Jones"
> escri
El 6 oct. 2017 19:13, "David Hugh-Jones"
escribió:
One question that comes to mind: what's the synergy? I e why are units and
errors best handled together? I use standard errors a lot, but never
units... I would like a standard way to represent uncertainty but don't
think I need the other stuff.
One question that comes to mind: what's the synergy? I e why are units and
errors best handled together? I use standard errors a lot, but never
units... I would like a standard way to represent uncertainty but don't
think I need the other stuff.
Cheers,
D
On Fri, 6 Oct 2017 at 17:25, Iñaki Úcar w
Dear all,
Edzer Pebesma and I are combining forces into a new GitHub
organisation called "r-quantities", to which we have moved the CRAN
packages 'units', 'errors' and 'constants'. The idea is to write a new
package called 'quantities' to integrate 'units' and 'errors' into a
comprehensive solutio
