On 2/07/20 11:24 am, Alexey Shipunov wrote:
I need to clarify. This part of example(dotchart) does not show group
labels in my case:
===
dotchart(VADeaths, main = "Death Rates in Virginia - 1940")
Ah! I see. I didn't know what I should be looking for in this
instance. Sorry for the
I need to clarify. This part of example(dotchart) does not show group
labels in my case:
===
dotchart(VADeaths, main = "Death Rates in Virginia - 1940")
===
My session is
===
> sessionInfo()
R version 4.0.2 (2020-06-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.6 LTS
On 2/07/20 2:58 am, Alexey Shipunov wrote:
Dear colleagues,
There is a new problem with dotchart(), and it is very simple to reproduce.
Just run example(dotchart).
On R versions < 4, group labels ("Urban Female" and so on) were
visible. Now they are not visible.
I just tried
Michael,
Thanks for the reminder on that.
Frederik, sometimes, with an emphasis on sometimes, the r-sig-* lists are
willing to go beyond narrow R programming assistance, and offer domain specific
conceptual assistance, which would otherwise be off-topic for r-help.
You might look through the
Thank you Michael!
> Op 1 jul. 2020, om 19:07 heeft Michael Dewey het
> volgende geschreven:
>
> Dear Frederik
>
> There is also a mailing list dedicated to meta-analysis in R
>
> https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis//
>
> Michael
>
>
> On 01/07/2020 16:40, Marc
Thank you Marc!
I ended up using metafor library:
res_UK <- escalc(mi=data_UK$GAD.7_mean, sdi=data_UK$weight_pred,
ni=data_UK$GAD.7_mean_N, measure = "MN”)
rma(yi, vi, data=res_UK, method="REML”)
> Op 1 jul. 2020, om 17:40 heeft Marc Schwartz het
> volgende geschreven:
>
> Hi,
>
> It
Dear Frederik
There is also a mailing list dedicated to meta-analysis in R
https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis//
Michael
On 01/07/2020 16:40, Marc Schwartz via R-help wrote:
Hi,
It sounds like you will want to engage in a meta-analysis.
There is a CRAN task view
I think you need to read about "faceting" in ggplot. This may necessitate
modifying your data structure.
?layout may be an alternative approach.
See also
https://cran.r-project.org/web/packages/egg/vignettes/Ecosystem.html
for a fuller exegesis.
Bert Gunter
"The trouble with having an open
r-help forum
Need some guidance. I need to create 20 plots and then combine them into one
graphic. Normally this isn't a problem for me except this time I'm using the
holts function to perform a TS forecast. So I though I'd just write a
function which take the country name and then passes the
Hi,
It sounds like you will want to engage in a meta-analysis.
There is a CRAN task view here:
https://cran.r-project.org/web/views/MetaAnalysis.html
that would be relevant in pointing you to tools in R that can support that
approach.
That being said, the details of specific methodologies
Hello everyone
I have some studies with results from the same outcome scale. I want to merge
them into 1 summarised estimated result and its standard deviation. How do I do
that in R?
Thank you very much for your help!
Frederik
__
Dear colleagues,
There is a new problem with dotchart(), and it is very simple to reproduce.
Just run example(dotchart).
On R versions < 4, group labels ("Urban Female" and so on) were
visible. Now they are not visible.
If in the dotchart() code, we replace the string
===
goffset <-
On Wed, 1 Jul 2020 15:24:35 +0200
Luigi Marongiu wrote:
>You are right: The vector X is actually Y -- the response I would like
>to fit the curve upon. I understood I should fit nls.lm with a
>function that describes the data (Holling or Gomperz), initial
>parameters, and the actual values (Y).
Addendum.
I have found the function Gompertz even better than the Holling III
because it gives more pronounced S profile. However the optimization
is bad even in this case:
```
gomp = function(p, x) {
y = p$a * exp(-p$b * exp(-p$c * x))
return(y)
}
A = 3261
B = 10
C = 1
X = c(8, 24, 39,
On Wed, 1 Jul 2020 14:31:19 +0200
Luigi Marongiu wrote:
> the optimization actually got a worse outcome than the original
>eyeball estimation
Could you elaborate on the function you are trying to fit to your data?
nls.lm takes a function returning a vector of residuals, that is,
fn <-
Thank you,
I got this:
```
holly = function(p, x) {
y = (p$a * x^2) / (p$b^2 + x^2)
return(y)
}
A = 3261
B = 10
K = CH$Cum_Dead[1:60]
X = c(8, 24, 39, 63, 89, 115, 153, 196, 242, 287, 344, 408, 473,
546, 619, 705, 794, 891, 999, 1096, 1242, 1363, 1506, 1648, 1753,
Hallo Martin
Yes I am aware of gradual improvement of R and also many new features of
version 4.0.x. I have to be more aware of fact that some code could work in one
version and give error in another, especially when using different major
versions.
Probably best option is to persuade IT
The basic problem is that holling() is not a (negative) loglikelihood function.
nll() _is_ a negative loglikelihood, but it is not clear for what. You appear
to be very confused as to what a likelihood even is (what is k? apparently your
response variable? Then how can it be a scalar if X is a
Hola David,
El mensaje de error indica el problema: las etiquetas de los chunks tienen que
ser únicas (lo que hay después de la r en el encabezado del chunk) Si has
copiado y pegado un chunk, cámbiale el identificador.
Un saludo,
Emilio L. Cano
http://emilio.lcano.com
> El 1 jul 2020, a
Buenas tardes,
Tengo un problema en el momento de dar click a *Knit *para generar un
documento *rmarkdown*.
Los pasos que he seguido son:
1. Cargar una tabla excel en *rmarkdown *siguiendo estos pasos:
a) File --> Import dataset --> Import excel
b) Copiar y pegar el comando en el chunk :
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