Hi Hadley,
actually, I started with floating point numbers, ensured that the
respective numbers are equal in R but I still got strange behaviour with
dplyr's group_by:
https://github.com/hadley/dplyr/issues/482
If I had to guess, I would suppose the source of this error somewhere in
the C++ part
When I call matrices from a function, they are called but are not
recognized as matrices. I use the code below. From the main function, when
I use the command is.matrix(), the response is FALSE. Why are the matrices
not recognized as matrices? Thanks in advance for any guidance.
#This function cre
On Fri, Jul 4, 2014 at 7:50 AM, João Azevedo Patrício
wrote:
> Hi,
>
> I've been trying to solve this issue but with no success.
>
> I have some data like this:
>
> 1 > TC WC
> 2 > 0 Instruments & Instrumentation; Nuclear Science & Technology;
> Physics, Particles & Fields; Spectroscopy
> 3 > 0
Hello,
My question is related to the rugarch package and its arfimafit function.
I am trying to fit an arfima(7,d,1) with an exogenous variable. Here is a
part of my code:
spec1<- arfimaspec(mean.model = list(armaOrder = c(7, 1), include.mean
=
FALSE,arfima = TRUE, ext
You can use:
print(dd1, row.names=F)
# Chisq DF Pr(>Chisq) term
153.0216306 1 7.578366e-35 # Sex
13.3696538 1 5.114571e-04 # Volume
0.8476713 1 7.144239e-01 # Weight
1.2196050 1 5.388764e-01 # Intensity
2.6349405 1 2.090719e-01 # ISO
6.0507714 1 2
Hi,
Try:
dat1 <- read.table(text="'1 > TC' 'WC'
'2 > 0' 'Instruments & Instrumentation; Nuclear Science & Technology;Physics,
Particles & Fields; Spectroscopy'
'3 > 0' 'Nanoscience & Nanotechnology; Materials Science,Multidisciplinary;
Physics, Applied'
'4 > 2' 'Physics, Nuclear; Physics, P
Em 04-07-2014 15:15, arun escreveu:
Hi,
Try:
dat1 <- read.table(text="'1 > TC' 'WC'
'2 > 0' 'Instruments & Instrumentation; Nuclear Science & Technology;Physics,
Particles & Fields; Spectroscopy'
'3 > 0' 'Nanoscience & Nanotechnology; Materials Science,Multidisciplinary;
Physics, Applied'
'4
On Jul 4, 2014, at 7:27 AM, Gang Chen wrote:
I really your kind help! This is exactly what I was looking for
except that I need to get rid of the numbered row names.
Look at the documentation:
?print.data.frame
You cannot "get rid of" rownames in dataframes (at least as far as I
know)
On 04/07/2014, 6:35 PM, Witold E Wolski wrote:
> how does a valid subscript (see first 2 lines) can produce an
> "subscript out of bounds" error (see line 4)?
>
>
> 1> sum(!rownames(msexp$rt) %in% msexp$pepinfo$transition_group_id)
> [1] 0
> 2> sum(!msexp$pepinfo$transition_group_id %in% rownames
On 04/07/2014, 6:35 PM, Witold E Wolski wrote:
> how does a valid subscript (see first 2 lines) can produce an
> "subscript out of bounds" error (see line 4)?
>
>
> 1> sum(!rownames(msexp$rt) %in% msexp$pepinfo$transition_group_id)
> [1] 0
> 2> sum(!msexp$pepinfo$transition_group_id %in% rownames
how does a valid subscript (see first 2 lines) can produce an
"subscript out of bounds" error (see line 4)?
1> sum(!rownames(msexp$rt) %in% msexp$pepinfo$transition_group_id)
[1] 0
2> sum(!msexp$pepinfo$transition_group_id %in% rownames(msexp$rt))
[1] 0
3> class(msexp$rt)
[1] "matrix"
4> msexp$rt
Actually the question is regarding differences in behaviour on windows in linux.
The 2 lines of code produce on linux all TRUE
on windows this looks "heterogenous"...
Using merge.data.frame produces on all platforms TRUE ...
> msexp$pepinfo =
> data.frame(merge(tt,msexp$pepinfo,by="transit
I used SMOTE algorithm in R for class balancing. My data size has
13000 rows, I had 7% minority class in my sample now I used SMOTE(
Synthetic Minority Oversampling Technique) for class balancing such
that I raised the ration of minority class to 42 % and number of rows
in data sample becomes 12655
Keep as numeric and group with cut(), Hmisc::cut2, or findInterval. The beauty
of the functional language design is that you do not need to create a new
factor variable.
--
David
Sent from my iPhone
> On Jul 4, 2014, at 8:33 AM, Hadley Wickham wrote:
>
> Why not just round the floating poin
Why not just round the floating point numbers to ensure they're equal
with zapsmall, round or signif?
Hadley
On Fri, Jul 4, 2014 at 4:04 AM, Sebastian Schubert
wrote:
> Hi,
>
> I would like to ask for best practice advice on the design of data
> structure and the connected analysis techniques.
>
I really your kind help! This is exactly what I was looking for except that I
need to get rid of the numbered row names.
On July 3, 2014 9:57:00 PM EDT, arun wrote:
>Hi,
>May be this helps:
>nC <- max(nchar(row.names(dd)))
>Â term <- formatC(row.names(dd), width=-nC)
>#or
>Â term <- sprintf("%-1
Hi
I would keep height as numeric and created height.f as factor, maybe ordered.
> hh<-runif(50)
> hh
[1] 0.116060220 0.447546370 0.433749570 0.006548963 0.425710667 0.328972894
[7] 0.091274539 0.271797166 0.007669982 0.208922146 0.168174196 0.227466231
...
hh.f<-cut(hh, seq(0,1,.1))
> hh.f
[1
Perfect! Thanks a lot!
On July 3, 2014 5:10:02 PM EDT, David L Carlson wrote:
>Not elegant, but it works:
>
>> term <- dimnames(dd)[[1]]
>> dd1 <- dd
>> dimnames(dd1)[[1]] <- rep("", 6)
>> dd2 <- capture.output(dd1)
>> cat(paste(dd2, " ", c("Term", term)), fill=48)
> # Chisq DF Pr(>Chisq)
No, Iâm sorry. Thatâs a mistake. I should have written:
row.active <- matrix(rbinom(K*steps, 1, .7), nr = K, nc = steps) == 1
so that this is a logical indexing vector, not just pulling out the first
element. To avoid yielding NaNs (though that doesnât really break the
question), Iâve
Hi,
I would like to ask for best practice advice on the design of data
structure and the connected analysis techniques.
In my particular case, I have measurements of several variables at
several, sometimes equal, heights. Following the tidy data approach of
Hadley Wickham, I want to put all data
Hi,
I've been trying to solve this issue but with no success.
I have some data like this:
1 > TC WC
2 > 0 Instruments & Instrumentation; Nuclear Science & Technology;
Physics, Particles & Fields; Spectroscopy
3 > 0 Nanoscience & Nanotechnology; Materials Science,
Multidisciplinary; Phys
Hi
Well, that is better.
This is what is expected
result<-cbind(v1,v2,v3)
I am not sure if such function solves your problem, as you have 50 variables.
fff<-function(v1, v2, v3, logic) {
res1<-v1
res2<-v2
res3<-v3
res1[logic] <- v1[logic]*2
res2[logic] <- 3*v3[logic]*res1[logic]
res3[logic] <-
Does anyone know how to extract the convergence code of an lmer object. I
am working in a monte carlo simulation with mixed model and I need to know
if a model has or not convergence. With unclass(mymodel) the following
information attr(,"optinfo")$conv$lme4 can be seen. How can I get this
importan
Hi all,
I finally managed to get Vennerable working with the help I got on the
forum. However, I'm faced with my next challange now.
The easy way to work with Vennerable works just fine, that is, if I enter
code like this:
Vdemo2 <- Venn(SetNames = c("foo", "bar"), Weight = c(`01`= 7, '11' = 8,
'1
On Thu, 3 Jul 2014 12:34:42 PM Marta valdes lopez wrote:
> Thank you Jim for your answer.Ok alpha( it is the speed of the boat) is
a
> range of number from 0.5 to 10 like 0.5,1,1.5,2, I would like to have
> the mean of x and y base on each value of alpha, because I have like
ten
> numbers of
Hi Frede,
awesome, thanks a lot. Helped me to understand how sammon is working as well.
Martin
On 4 July 2014 10:02, Frede Aakmann Tøgersen wrote:
> Hi
>
> It seems to be related to the way that the default start values (y argument
> of sammon) are calculated.
>
> Here the last two rows are th
There are books on this, can't repeat them here...
Roughly speaking, Fisher Scoring is quadratically convergent, hence requires
much fewer iterations than gradient descent methods which are generally only
linear, and sometimes very slowly so (in highly collinear cases, usually).
I.e., it is a m
Hi
Not much helpful. Now we know what you ***think*** alpha is but not what it
really is.
You shall post at least result of
str(your.objects)
I also wonder why do you populate slots in perf manually and with data.frames
instead of lists which are required according to documentation.
Regards
Hi.
Well, Case is probably factor, which is basically numeric vector with labels.
It is useful for some operations but it can have some features which lead to
this behaviour. I do not have available your exact code but I presume you use c
or cbind somewhere.
> Case<-factor(letters[1:4])
> Case
Hi
It seems to be related to the way that the default start values (y argument of
sammon) are calculated.
Here the last two rows are the same:
> cmdscale(dist(data), 2)
[,1] [,2]
c1 2.04910556 -0.3627887
c2 -0.01889892 -0.1822057
c3 0.40767629 0.2599026
c4 0.81569304 -0
Hi
Are you 100% sure that you always want select only first item from v1,v2 and v3
and change it in each step of cycle and keep only last value from your cycle in
first item in vectors v1-3?
Because this is what your cycle does.
Petr
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r
Hi all,
the sammon mapping fails with message "initial configuration has
duplicates". But there are no duplicates in my data (see example
below).
Apparently, the problem is that row 9 and 10 have an equal distance to
all other rows (but they are not equal, see last two columns).
Any help to get s
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