The solution proposed below does not accomplish my goal. In the column
labeled NEW_VALUE, there are two NAs where the value in NUMERIC_VALUE for
that row should be.
Can anyone else suggest a solution to my problem?
Thanks!
On Sat, Mar 18, 2017 at 1:33 PM, David Winsemius
wrote:
>
> > On Mar 1
Hello, I am having some troubles extracting pixels from a raster using
polygons. When I attempt to do so, pixels which are only partially
intersected by polygons are not included.
In the example below the number of pixels returned is less than the number
of pixels which can be seen intersecting po
Dear R-Help readers,
I am writing to ask about some behavior of base::dimnames() that surprised
me. If I create an array with one of its dimensions = 1, and then try to
assign names to that dimension, I get an error unless I name one of the
other dimensions first. For example:
> temp1 = array(NA,
Hi Guillaume,
If you are talking about the "Bubble Chart", you might be able to use
the boxed.labels function in plotrix. Here is a slight modification of
the first example for the size_n_color function that may help.
library(plotrix)
meantemp<-c(19,22,25,29,21,20,16,27,23,26)
totalrain<-c(174,
It is confusing, but he is comparing STATA package xtabond2 with R packages plm
and panelvar. For example:
"The same example with out [sic] code reads as follows:
R> library(panelvar)
R> library(plm)
R> data("abdata")"
Suggests that panelvar is an R package, but apparently one that is not
publi
> On Mar 20, 2017, at 12:21 PM, David Winsemius wrote:
>
>
>> On Mar 20, 2017, at 10:18 AM, David L Carlson wrote:
>>
>> I had no clue either, but consulting the oracle known as "google" with the
>> query: "panel var in r" produced links to a recent paper by Sigmund et al
>> called "Panel V
> On Mar 20, 2017, at 10:18 AM, David L Carlson wrote:
>
> I had no clue either, but consulting the oracle known as "google" with the
> query: "panel var in r" produced links to a recent paper by Sigmund et al
> called "Panel Vector Autoregression in R: The panelvar Package."
>
> However the
Hi,
I'm trying to draw a chart such as the one provided by gvisOrgChart in the
GoogleVis demo, that would provide more options such as boxes with varying size
or the ability to add basic statistics on each subgroup represented by a box.
Any idea ?
Thanks
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What did
https://www.google.de/search?q=Panel+VAR+R
show?
el
On 2017-03-20 12:50 , Abhishek Kumar Rohit wrote:
> Is there any package available for estimating Panel VAR. Can the packages
> vars and palm be combined in some way to do that?
>
> Regards,
> *Abhishek Rohit*
> Research Fellow
> IIM
I had no clue either, but consulting the oracle known as "google" with the
query: "panel var in r" produced links to a recent paper by Sigmund et al
called "Panel Vector Autoregression in R: The panelvar Package."
However the package does not seem to be available on CRAN so you'll have to
conta
Here is a version similar to Rui's, but using ave() and logical
indexing to simplify a bit:
> DF4[with(DF4, ave(as.numeric(var), city, FUN = function(x)length(unique(x)))
> ==1), ]
city wk var
4 city2 1 x
5 city2 2 x
6 city2 3 x
7 city2 4 x
8 city3 1 x
9 city3 2 x
10
Excuse my denseness, but huh??
If you receive no satisfactory responses, please read the posting
guide to learn how to post an intelligible question.
Otherwise, just ignore me.
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things
Is there any package available for estimating Panel VAR. Can the packages
vars and palm be combined in some way to do that?
Regards,
*Abhishek Rohit*
Research Fellow
IIM Raipur
[[alternative HTML version deleted]]
__
R-help@r-project.org mailin
I am contributing to a session at userR 2017 this coming July that will
focus on discovering and learning about R packages. This is an increasingly
important issue for R users as we all decide which of the 10,000+ packages
to invest time in understanding and then use in our work.
To prepare for th
Hello there!!
Could somebody please go through the question (
http://stats.stackexchange.com/questions/268323/string-kernels-in-r)?
In short I need the reference to the algorithms used for string kernels in
Kernlab package in R.
Thank you.
Regards:
Rahul
[[alternative HTML version del
Private, because off topic.
Thierry:
I believe your advice is incorrect. The imputation and model fitting
*must* be included as part of the bootstrap sampling -- that is, you
must fit and multiple impute for each bootstrap sample as that mimics
what you did with the original sample. Your procedu
> On Mar 20, 2017, at 4:42 AM, Troels Ring wrote:
>
> Dear friends - here is an example of something that I find annoying
>
> library(ggplot2)
> DDF <- data.frame(x=x<-seq(1,10),y=x^2)
> G <- ggplot(data=DDF,aes(x=x,y=y)) + geom_point()
> GG<-G+ylab(expression(paste("Total ",CO[2]," halved")))
Dear friends - here is an example of something that I find annoying
library(ggplot2)
DDF <- data.frame(x=x<-seq(1,10),y=x^2)
G <- ggplot(data=DDF,aes(x=x,y=y)) + geom_point()
GG<-G+ylab(expression(paste("Total ",CO[2]," halved")))
GG
GG+annotate("text",x=5,y=50,label=expression(paste("Total ",CO[
The fact related to Rolf's vague recollection is here:
https://stat.ethz.ch/pipermail/r-help/2015-March/426799.html
And the relevant post (Martin Maechler's answer):
https://stat.ethz.ch/pipermail/r-help/2015-March/426834.html
Should that be a FAQ?
Helios
> On 16/03/17 03:57, Bert Gunter wrot
Dear David,
Please have a look at our multimput package
(https://github.com/inbo/multimput). It handles multiple imputation
based on generalised linear mixed models. Currently based on either
glmer (lme4) and inla (INLA) . After imputation you can apply any
model or function you like. So you could
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