dear JN,
Thanks for the reply. I will consider using the nlsr package.
But for now I make did with reducing the exponent. It is working for me.
very many thanks for your time and effort
yours sincerely,
AKSHAY M KULKARNI
From: J C Nash
Sent:
On Thu, 7 Mar 2019, Sparks, John wrote:
Thanks to Achim's direction I now have a re-producible example.
The code below creates a ts object. The x scale of the last graph runs
from 0 to 700.
Yes, and hence breakpoints() re-uses that scaling. As I wrote in my
previous mail you either have
Hi All,
So I finally made the jump to polymode. Still getting use to the changes after
having used ESS for circa 15 years or so on Windows, Linux and OSX/macOS.
Thanks to those involved in developing and maintaining polymode.
Three questions:
1. While the syntax highlighting seems to be
Thanks to Achim's direction I now have a re-producible example.
The code below creates a ts object. The x scale of the last graph runs from 0
to 700.
So just need a way to get that scale to show the weeks (or some summary of
them).
Thanks a bunch.
--JJS
library(strucchange)
library(xts)
On Thu, 7 Mar 2019, Sparks, John wrote:
Hi R Helpers,
I am doing some work at identifying change points in time series data.
A very nice example is given in the R Bloggers post
https://www.r-bloggers.com/a-look-at-strucchange-and-segmented/
The data for the aswan dam in that example is
Hi John,
You seem to have 1569 days of data, so perhaps you can get around your
axis problem like this:
plot(Nile,xaxt="n",xlab="Week")
...
axis(1,at=seq(0,200,50),labels=seq(0,200,50)*7)
(untested)
Jim
On Thu, Mar 7, 2019 at 10:46 AM Sparks, John wrote:
>
> Hi R Helpers,
>
> I am doing some
rlang works with R 3.1 and up, but it does require compilation from
source, which I suspect is the root cause of this problem.
Hadley
On Wed, Mar 6, 2019 at 5:36 PM peter dalgaard wrote:
>
> Also, R seems to be version 3.2.x i.e. 3-4 years old. Earliest rlang is anno
> 2017 as far as I can
Hi R Helpers,
I am doing some work at identifying change points in time series data. A very
nice example is given in the R Bloggers post
https://www.r-bloggers.com/a-look-at-strucchange-and-segmented/
The data for the aswan dam in that example is yearly. My data is weekly. I
ran the code
Also, R seems to be version 3.2.x i.e. 3-4 years old. Earliest rlang is anno
2017 as far as I can tell.
-pd
> On 6 Mar 2019, at 19:22 , Norberto Hernandez
> wrote:
>
> I have the same issue with ggplot2 and the rlang package, you need to
> have the most updated version of the rlang library
Also, I forgot that tmap can do interactive maps, see:
https://geocompr.robinlovelace.net/adv-map.html#interactive-maps
-Roy
> On Mar 6, 2019, at 2:48 PM, Roy Mendelssohn - NOAA Federal
> wrote:
>
> see https://r-spatial.github.io/mapview/index.html
>
> The main thing is the data types
see https://r-spatial.github.io/mapview/index.html
The main thing is the data types that map view supports, so you must have a
raster or an spatial object like an "sf" object. So points would have to also
be an sf object and the two combined (sf has commands to do this) or perhaps
you can
Roy
Thank you - that's helpful. Going to have to read up on sf and mapview
library. Those are new ones. Then to add a point feature layer (lat/long)
where would I insert that?
Library(maps)
Library(sf) # simple features
Library(mapview)
world.map <- maps::map("world", plot = FALSE, fill =
Or if you prefer plotly:
world.map <- maps::map("world", plot = FALSE, fill = TRUE)
p <- sf:: st_as_sf(world.map, coords = c('x', 'y'))
plotly::ggplotly(
ggplot2::ggplot(data = p) + ggplot2::geom_sf()
)
> On Mar 6, 2019, at 2:12 PM, Roy Mendelssohn - NOAA Federal
> wrote:
>
> world.map <-
world.map <- maps::map("world", plot = FALSE, fill = TRUE)
p <- sf:: st_as_sf(world.map, coords = c('x', 'y'))
map view::map view(p)
HTH,
-Roy
> On Mar 6, 2019, at 2:10 PM, rmendelss gmail wrote:
>
> world.map <- maps::map("world", plot = FALSE, fill = TRUE)
> p <- sf:: st_as_sf(world.map,
R Help
Anyone know if I can add a zoom In/Out function to the maps available via the
"maps" library? Or do I need to use a different mapping library?
world.map <- map_data("world")
ggplot(data = world.map) +
geom_polygon(mapping = aes(x=long, y=lat, group=group))
Jeff
I have the same issue with ggplot2 and the rlang package, you need to
have the most updated version of the rlang library in order to get
installed ggplot2
Regards
Norberto
El mar., 5 mar. 2019 a las 14:24, Jeff Newmiller
() escribió:
>
> Please post the text version of the error in the future...
nls() is a Model T Ford trying to drive on the Interstate. The code
is quite old and uses approximations that work well when the user
provides a reasonable problem, but in cases where there are mixed large
and small numbers like yours could get into trouble.
Duncan Murdoch and I prepared the nlsr
R is open source so you can look at the code.
In this case just typing the function name gets it:
> p.adjust
function (p, method = p.adjust.methods, n = length(p))
{
method <- match.arg(method)
if (method == "fdr")
method <- "BH"
. . . . . Stuff deleted . . . .
# The code
Gracias
On Wed, 6 Mar 2019 at 15:47, Xavier-Andoni Tibau Alberdi <
xaviti...@gmail.com> wrote:
> Pues ahí lo tienes. Usa %in% para ver si esta en ese grupo, y en caso de
> estarlo pones el nombre del grupo. Aquí un ejemplo.
> https://www.datamentor.io/r-programming/ifelse-function/
>
> Saludos,
Si lo que quiero es crear una variable llamada por ejemplo region (del tipo
factor) con esos 5 valores
On Wed, 6 Mar 2019 at 15:41, Xavier-Andoni Tibau Alberdi <
xaviti...@gmail.com> wrote:
> No, No. Fíjate en el Ifelse(condición, valor si positivo, valor si
> negativo).
>
> Si, x %in% ca
Con R base:
paises <- factor(c("a", "b", "c", "c", "a"))
zonas <- c("norte", "norte", "sur")
names(zonas) <- c("a", "b", "c")
zonas_paises <- paises
levels(zonas_paises) <- zonas[levels(zonas_paises)]
zonas_paises
Un saludo,
Carlos J. Gil Bellosta
http://www.datanalytics.com
El mié., 6 mar.
Pues ahí lo tienes. Usa %in% para ver si esta en ese grupo, y en caso de
estarlo pones el nombre del grupo. Aquí un ejemplo.
https://www.datamentor.io/r-programming/ifelse-function/
Saludos,
Xavi
Missatge de Antonio Rodriguez Andres
del dia dc., 6 de març 2019 a les 15:44:
> Si lo que quiero
No, No. Fíjate en el Ifelse(condición, valor si positivo, valor si
negativo).
Si, x %in% ca entonces el valor devuelto es "ca", un factor. En caso
negativo, vamos al siguiente bloque iflese, que comprueba si el país esta
en el siguiente grupo, na. Si está en na nos devuelve "na". Vamos, que la
Pero eso es para crear variables binarias tipo 0-1 si el pais pertence a un
determinado grupo. Lo que quiero es crear una variable de tipo factor con
esos 5 niveles, sabiendo que tengo en el dataframe una variable llamada
Country, con el nombre del pais.
Gracias
On Wed, 6 Mar 2019 at 15:27,
Buenas,
Para ello yo uso el operador %in%, que me dice si algo esta dentro de un
vector. Luego hago bucles de if else, pero usando la función iflese(). Si
país X esta en países lista ca, entonces "ca",etc. Puedes crear una función
que englobe ese iflese(), para aplicarla para cada columna del
Hola estimados miembros de la comunidad de R
Tengo un conjunto de datos, donde tengo observaciones por países y por año.
Una de las variables del dataframe es el nombre del país. Queremos dividir
los países, que son países africanos de acuerdo a 5 regiones: norte de
africa, africa del este, sur
Dear everybody,
I'm using stats package (version 3.5.2) and in detail their p.adjust()
function in order to control the false discovery rate in multiple
comparisons. In particular I used the Benjamini-Hochberg method.
Nevertheless, the help of the stats package indicates that the adjusting
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