Hi,
I wrote and maintain the Thresher package. It includes code to do
simulations. In the "tests" directory of the package, I do some simple
simulations and run the main algorithm, then write out summaries of the
results
The initial submission of the package to CRAN was delayed because the
On 17/05/2018 11:53 AM, Martin Maechler wrote:
Kevin Coombes
on Thu, 17 May 2018 11:21:23 -0400 writes:
> Hi, I wrote and maintain the Thresher package. It includes
> code to do simulations. In the "tests" directory of the
> package, I do some
> Kevin Coombes
> on Thu, 17 May 2018 11:21:23 -0400 writes:
> Hi, I wrote and maintain the Thresher package. It includes
> code to do simulations. In the "tests" directory of the
> package, I do some simple simulations and run the main
>
On 17/05/2018 11:51 AM, Brian G. Peterson wrote:
newer versions of R require importFrom for functions from 'stats',
'graphics' and many other packages that used to be assumed to be on the
search path and thus available.
'methods' continues to have seemingly different treatment.
If you try to
newer versions of R require importFrom for functions from 'stats',
'graphics' and many other packages that used to be assumed to be on the
search path and thus available.
'methods' continues to have seemingly different treatment.
If you try to use importFrom to import a single function (in this
On 05/17/2018 11:59 AM, Duncan Murdoch wrote:
On 17/05/2018 11:51 AM, Brian G. Peterson wrote:
newer versions of R require importFrom for functions from 'stats',
'graphics' and many other packages that used to be assumed to be on the
search path and thus available.
'methods' continues to
> Duncan Murdoch
> on Thu, 17 May 2018 12:13:01 -0400 writes:
> On 17/05/2018 11:53 AM, Martin Maechler wrote:
>>> Kevin Coombes ... on Thu, 17
>>> May 2018 11:21:23 -0400 writes:
>>[..]
>> > [3] Should the documentation (man
What's the best way to document an S4 method that takes arguments
beyond those in the signature?
Consider
setGeneric("sim", function(simP, dataP, ...) standardGeneric("sim"))
setMethod("sim", signature="SimParameters", function(simP, dataP) {
lapply(seq(simP@NIter), function(i) do.one(simP,
There have been various comments in this thread (by me, and I think
Duncan Murdoch) about how you can identify the platform you're running
on (some combination of .Platform and/or R.Version()) and use it to
write conditional statements so that your tests will only be compared
with reference values
But why would you want to tie your tests to specific platforms, if
mathematically all those results are equivalent? You could compare the
orthogonal complements from a full rank matrix (say the identity) to each
expected eigenspace. E.g., for the example I gave above, where e2 and e1
gave
Yes; I'm pretty sure that it is exactly the repeated eigenvalues that are
the issue. The matrices I am using are all nonsingular, and the various
algorithms have no problem computing the eigenvalues correctly (up to
numerical errors that I can bound and thus account for on tests by rounding
Yes; but I have been running around all day without time to sit down and
try them. The suggestions make sense, and I'm looking forward to
implementing them.
On Thu, May 17, 2018, 3:55 PM Ben Bolker wrote:
> There have been various comments in this thread (by me, and I think
>
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