Before posting on the r-help list I did run Rprof(). In my posting I asked
for help with re-writing the specific script into sapply() or
foreach()/doParallel format.
Thanks anyway for your time and suggestions,
Lexo
On Thu, Jan 24, 2019 at 12:38 AM Eric Berger wrote:
> Charles writes about
Dear Bill,
Appreciate all your effort. I hope some one here can respond to this query.
Many thanks,
Ashim
On Thu, Jan 24, 2019 at 12:49 AM Bill Poling wrote:
>
> Ashim.
>
> I see where I was mistaken, using MARSSparamsCIs(fit) <--Somehow I got an
> s in between param & Cis.
>
> I now get
Hi Jeff;
I figured out the problem. I do apologize to you and members in the list to
bother you with this simple problem.
Regards,
Greg
On Wed, Jan 23, 2019 at 6:46 PM Jeff Newmiller
wrote:
> Problem is in your data not matching your values, but you did not share
> your data. Try using the
Problem is in your data not matching your values, but you did not share your
data. Try using the unique() function to see what values you have in your data.
I will say that when I want to assign discrete colors I always start by
converting my character column in the data frame to a factor and
Hi Dear all;
I am getting the "sufficient values in manual scale. 10 needed but only 7
provided." problem when running the followings. Your help is highly
appreciated.
Regards,
Greg
p2<-p1+scale_color_manual(name="Diseases",
labels=c("Myocardial Infarction", "Coronary artery disease", "Stroke",
Something like
files <- list.files(pattern="*.xls", full.names = TRUE)
data <- lapply(files, read_excel, sheet="Flow Data", range=("b9:c10"))
should do it.
--Ista
On Wed, Jan 23, 2019 at 12:42 PM Thomas Subia via R-help
wrote:
>
>
> Colleagues,
>
> I have a workbook which has 3 worksheets
>
Charles writes about saving execution time by eliminating redundancies.
If you see redundancies related to calling a time-consuming function
multiple times with the same arguments, a very easy way to speed up your
program is to memoise the functions using the package memoise.
HTH,
Eric
On
Ashim.
I see where I was mistaken, using MARSSparamsCIs(fit) <--Somehow I got an s in
between param & Cis.
I now get new error similarly as you, my apologies.
final <- MARSSparamCIs(fit)
Error in dpari[time.varying] <- dparmat(MLEobj, time.varying, t = t) :
replacement has length zero
sessionInfo()
#R version 3.5.2 (2018-12-20)
#Platform: x86_64-w64-mingw32/x64 (64-bit)
#Running under: Windows >= 8 x64 (build 9200)
Hello Ashim. I am not familiar with the MARSS pkg, however, I am always
interested in following many of these R-Help questions and often run them for
my own
On 23/01/2019 12:27 p.m., AbouEl-Makarim Aboueissa wrote:
here is the messages I got when I install the "car" package:
You didn't install it, you got errors during the install.
I'm not sure why there was no attempt to install Rcpp (which was
required by rio, see the error message). Perhaps
See inline.
> On Jan 23, 2019, at 2:17 AM, Aleksandre Gavashelishvili
> wrote:
>
> I'm trying to speed up a script that otherwise takes days to handle larger
> data sets. So, is there a way to completely vectorize or paralellize the
> following script:
>
>*# k-fold cross
I'd recommend you upgrade to R version 3.5.2, the version you have is quite
out of date.
On Wed, Jan 23, 2019 at 9:42 AM AbouEl-Makarim Aboueissa <
abouelmakarim1...@gmail.com> wrote:
> here is the messages I got when I install the "car" package:
>
> > install.packages("car")
> Installing
Colleagues,
I have a workbook which has 3 worksheets
I need to extract data from two specific cells from one ofthose worksheets.
I can use read_excel to do this for one file.
data<-read_excel("C:/Desktop/Excel_raw_data/0020-49785 8768.xls",
sheet="Flow
here is the messages I got when I install the "car" package:
> install.packages("car")
Installing package into ‘C:/Users/aaboueissa/Documents/R/win-library/3.3’
(as ‘lib’ is unspecified)
also installing the dependency ‘rio’
There are binary versions available but the source versions are
Hi Duncan,
On Wed, Jan 23, 2019 at 10:02:00AM -0500, Duncan Murdoch wrote:
> On 23/01/2019 5:27 a.m., Jan T Kim wrote:
> >Hi Ivan & All,
> >
> >R's scoping system basically goes to all environments along the call
> >stack when trying to resolve an unbound variable, see the language
> >definition
On 23/01/2019 12:13 p.m., AbouEl-Makarim Aboueissa wrote:
Dear All:
After installing the packages "car" and "alr3", I got the following error
messages:
library(car)
Error in library(car) : there is no package called ‘car’
library(alr3)
Error in library(alr3) : there is no package called
Dear All:
After installing the packages "car" and "alr3", I got the following error
messages:
> library(car)
Error in library(car) : there is no package called ‘car’
> library(alr3)
Error in library(alr3) : there is no package called ‘alr3’
any helps would be appreciated.
with many thanks
I'm trying to speed up a script that otherwise takes days to handle larger
data sets. So, is there a way to completely vectorize or paralellize the
following script:
*# k-fold cross validation*
df <- trees # a data frame 'trees' from R.
df <- df[sample(nrow(df)), ] # randomly
Also quantile() and cut(). The only tricky part is making sure the minimum and
maximum values are included.
> set.seed(42)
> x <- rnorm(100, 25, 3)
> bks <- quantile(x, prob=c(0, .2, .4, .6, .8, 1))
> y <- cut(x, breaks=bks, labels=1:5, include.lowest=TRUE)
> table(y)
y
1 2 3 4 5
20 20 20
On 23/01/2019 5:27 a.m., Jan T Kim wrote:
Hi Ivan & All,
R's scoping system basically goes to all environments along the call
stack when trying to resolve an unbound variable, see the language
definition [1], section 4.3.4, and perhaps also 2.1.5.
You are misinterpreting that section. It's
On 23/01/2019 4:53 a.m., Ivan Krylov wrote:
Hi!
I needed to generalize a loss function being optimized inside another
function, so I made it a function argument with a default value. It
worked without problems, but later I noticed that the inner function,
despite being defined in the function
Hi akshay Kulkarni, I just worked through this great tutorial the other day,
hope this helps!
WHP
https://www.r-bloggers.com/how-to-combine-multiple-ggplot-plots-to-make-publication-ready-plots/
From: R-help On Behalf Of Eric Berger
Sent: Tuesday, January 22, 2019 8:59 AM
To: PIKAL Petr
Hi,
There's something strange going on with the R help buffers. I'm using
the latest ess-20190122.2108 from melpa, but it's not particular to that
version:
I want each help buffer to appear in its own separate frame, and have
'(ess-help-own-frame t)
'(ess-help-reuse-window nil)
in my
Hi Ivan & All,
R's scoping system basically goes to all environments along the call
stack when trying to resolve an unbound variable, see the language
definition [1], section 4.3.4, and perhaps also 2.1.5.
Generally, unbound variables should be used with care. It's a bit
difficult to decide
Hi!
I needed to generalize a loss function being optimized inside another
function, so I made it a function argument with a default value. It
worked without problems, but later I noticed that the inner function,
despite being defined in the function arguments, somehow closes over a
variable
Hi
Yes, you should get multipage pdf, each page populated by single call to plot
function.
However I am not sur if your proposal with function will work.
I usually do simply
pdf("sample.pdf", 7, 5)
for (i in 1:n) {
hist(L[[i]])
}
dev.off()
Cheers
Petr
From: akshay kulkarni
Sent:
cut can do the job
q_prob <- seq(0, 1, 0.2)
cut(x, breaks = quantile(x, probs = q_prob), include.lowest = T , labels =
1:5)
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