> On May 3, 2018, at 6:28 PM, sunyeping via R-help wrote:
>
> When I check the size of the plot region usingdev.size("in")a new plot region
> is produced and in the Rconsole I get[1] 5.33 5.322917
Your test is all mangleed together. You failed in your duty to read the list
info and the Po
When I check the size of the plot region usingdev.size("in")a new plot region
is produced and in the Rconsole I get[1] 5.33 5.322917If I mean to produce
a plot region with size setting bydev.new(length=3,width=3)a plot region is
produced, but the size is [2.281250, 5.322917], as detected by
On Thu, May 3, 2018 at 2:03 PM, Michael Ashton
wrote:
> Thanks Bert. But everyone on that forum wants to use finance tools rather
> than general optimization stuff! And I am not optimizing a traditional
> Markowitz mean-variance problem. Plus, smarter people here. :-)
>
I'm very confused by thes
If you require that the 'type' column be a factor with a level for each
element of the input list, then you need to do that after calling
dplyr::bind_rows(), just as with the base-R solutions.
> l <- list( A = data.frame(X=1:2, Y=11:12), B = data.frame(X=integer(),
Y=integer()), C = data.frame(X=3
This looks like what I call a sumscale problem i.e., some sort of simple
function of the parameters sums to a constant. I've done some work on
these, but don't have it with me just now. There are several approaches,
but they can be quite tricky. Will send some info in about a week or so
if you are
> On May 3, 2018, at 10:52 AM, Michael Ashton
> wrote:
>
> Hi –
>
> This is giving me a headache. I’m trying to do a relatively simple
> optimization – actually trying to approximate the output from the Excel
> Solver function but at roughly 1000x the speed. 😊
>
> The optimization parameter
Thanks Bert. But everyone on that forum wants to use finance tools rather than
general optimization stuff! And I am not optimizing a traditional Markowitz
mean-variance problem. Plus, smarter people here. :-)
> On May 3, 2018, at 3:01 PM, Bert Gunter wrote:
>
> You can't -- at least as I read
You can't -- at least as I read the docs for ?optim (but I'm pretty
ignorant about this, so maybe there's a way to tweak it so you can).
See here: https://cran.r-project.org/web/views/Optimization.html
for other R optimization capabilities.
Also, given your credentials, the r-sig-finance list
The r-sig-mixed-models list would be a better place for this post if
you do not get an answer here.
Cheers,
Bert
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 his "Bloom County" comic strip )
Hi,
my question is probably amateurish but I can't seem to find the answer
anywhere.
In what metric are the MCMCglmm package's posterior means for family =
"categorical"?
I suppose that they can't be odds ratios and probabilites as my numbers are
outside their bounds. So I'm thinking – are they
On 05/03/2018 01:28 PM, Hadley Wickham wrote:
On Wed, May 2, 2018 at 11:53 AM, Jeff Newmiller
wrote:
Another approach:
library(tidyr)
L <- list( A = data.frame( x=1:2, y=3:4 )
, B = data.frame( x=5:6, y=7:8 )
)
D <- data.frame( Type = names( L )
, s
Hi –
This is giving me a headache. I’m trying to do a relatively simple optimization
– actually trying to approximate the output from the Excel Solver function but
at roughly 1000x the speed. 😊
The optimization parameters look like this. The only trouble is that I want to
add a constraint that
On Wed, May 2, 2018 at 11:53 AM, Jeff Newmiller
wrote:
> Another approach:
>
>
> library(tidyr)
> L <- list( A = data.frame( x=1:2, y=3:4 )
> , B = data.frame( x=5:6, y=7:8 )
> )
> D <- data.frame( Type = names( L )
>, stringsAsFactors = FALSE
>
> On May 2, 2018, at 2:43 PM, David L Carlson wrote:
>
> Typo: dat[[z]] should be x[[z]]:
>
> x2 <- do.call(rbind, lapply(names(x), function(z)
> data.frame(type=z, x[[z]])))
> x2
> type x y
> 1A 1 3
> 2A 2 4
> 3B 5 7
> 4B 6 8
Sometimes one want to "bind" list that have
Thanks,
I always get confused by expression evaluation, when and how to use call,
do.call, eval, parse/deparse, and all that good stuff. I always have to read
documentation 10 times and still does not want to stick in my brain.
- Original Message -
From: "Bert Gunter"
To: "Sebastien Bi
First of all, your message is a little hard to read because you posted
in HTML. This list removes the HTML, and often mangles messages, so you
should always post in plain text. But in this case your message was
still pretty readable.
On 02/05/2018 11:04 PM, Andrew Hoerner wrote:
Dear R Help
On 05/03/2018 03:59 AM, Martin Maechler wrote:
David L Carlson
on Wed, 2 May 2018 21:43:52 + writes:
Typo: dat[[z]] should be x[[z]]:
x2 <- do.call(rbind, lapply(names(x), function(z)
data.frame(type=z, x[[z]])))
x2
type x y
1A 1 3
2A 2 4
3
Hi,
I believe that Caret uses a grid-serach approach. I was wondering if:
1 There are more efficient implementations for HP tuning for classification
algos (eg XGboost, CatBoost, SVM, RF etc), using say GM/SWARM approaches, akin
to Google's approach AutoML for Image related Net problems?
2 This
library(sos)
(mp <- findFn('{molecular properties}'))
** found 7 matches in 4 packages and opened two web pages in my
default browser with (a) the 7 matches and (b) the 4 packages. The first
function was something for amino acids, like you suggested. Two others
returned compound and
> David L Carlson
> on Wed, 2 May 2018 21:43:52 + writes:
> Typo: dat[[z]] should be x[[z]]:
>
> x2 <- do.call(rbind, lapply(names(x), function(z)
> data.frame(type=z, x[[z]])))
> x2
> type x y
> 1A 1 3
> 2A 2 4
> 3B 5 7
> 4B 6 8
>
All
Is there a package or library that will, given a nucleotide sequence
1. calculate the extinction coefficient at 260 nm for (Beer-Lambert's law)
2. calculate molecular weight
3. return it's complementary sequence
I was able to find several packages that can do similar calculations for an
a
On 05/03/2018 07:58 AM, Jeff Newmiller wrote:
This is very nice to learn about, Denis, but it seems only fair to point out
that the result of rbindlist is not a data frame. You can convert it to a data
frame easily, but the copy and indexing semantics of data tables are quite
different than
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