(excerpts only)
> Using this file, with the tab for Growth_Value (I have pasted some code
> below), if I add the argument *exact = F *it produces the Wilcoxon signed
> rank test with continuity correction. The description documentation leads
> me to believe that's the wrong argument (should be the
Sorry.
Some more comments.
(1) If you want an arbitrary sample size, you may need to write a function
to produce a simulated data set, for that given sample size.
Alternatively, you can use a random sample of size n, of an initial data
set, assuming the initial data set is relatively large.
(2) Fo
Hello all,
I am trying to port some R code over to Python for someone else. In
particular, I want to save a model/object created using the train function
from the caret package:
model <- train(
x, y,
trControl = trcontrol_1,
tuneGrid = xgbGrid_1,
method = "xgbTree"
)
'model' is l
Good afternoon,
Using this file, with the tab for Growth_Value (I have pasted some code
below), if I add the argument *exact = F *it produces the Wilcoxon signed
rank test with continuity correction. The description documentation leads
me to believe that's the wrong argument (should be the "corre
> How can I modify my R codes to simulate the sample size, the presence of
Y-outliers and the presence of missing data ?
I don't know what it means for data to have 50% Y-outliers.
That's new to me...
As for the rest of your question.
Modify your code so that a single function, say sim.test() com
Hi Ana,
Or just for a bit of fun:
pt<-read.table(text="eidQ phenoQ phenoH
117 -9 -9
125 -9 -9
138 -9 1
142 -9 -9
156 -9 -9
174 -9 -9
138 -9 1
1000127 2 1
1000690 2 -9
1000711 2
The ifelse() construction is fast, but after a couple of nested iterations,
it gets messy and error-prone; so I believe to be avoided.
In your case, there is a much better alternative, ?pmax . Ergo, something
like:
pt$pheno <- do.call(pmax, pt[, -1])
?do.call is necessary to pass the list of col
pmax() should work in this instance, as in any case you want the larger value.
Andrew
--
Andrew Robinson
Director, CEBRA, School of BioSciences
Reader & Associate Professor in Applied Statistics Tel: (+61) 0403 138 955
School of Mathematics and Statistics Fax: (+61) 03 8344 4599
University of Mel
does this look ok:
pt$pheno=ifelse(pt$phenoQ==-9 & pt$phenoH==-9,-9,ifelse(pt$phenoH==2 |
pt$phenoQ==2,2,1))
On Wed, Aug 7, 2019 at 1:40 PM Ana Marija wrote:
>
> Hello,
>
> I have a data frame which looks like this:
>
> > head(pt)
> eidQ phenoQ phenoH
> 1 117 -9 -9
> 2 125
Hello,
I have a data frame which looks like this:
> head(pt)
eidQ phenoQ phenoH
1 117 -9 -9
2 125 -9 -9
3 138 -9 1
4 142 -9 -9
5 156 -9 -9
6 174 -9 -9
7 138 -9 1
8 1000127 2 1
9 1000690 2
Hi Sigbert
Here is something that has both the sliderTextInput and Radio Buttons,
which may be helpful:
library("shiny")
library("shinyWidgets")
ui <- fluidPage(
br(),
sliderTextInput(
inputId = "mySliderText",
label = "My House",
choices = list("choice 1" = "choice 1","c
Dear all,
I'm using *rugarch* and *rmgarch *to implement a DCC model over 30
different assets.
While using *ugarchspec *for defining input parameters of univariate GARCH
using a t-Student distribution, I have noticed that there is a parameter
called *fixed.pars*. Using the example given in GitHub,
ethnobotanyR 0.1.5 is a patch. The package now includes four new functions:
Updated UVs() following Tardio and Pardo-de-Santayana (2008)
simple_UVs() now calculates a simple UVs cf. Albuquerque et al. (2006).
Fidelity level per species FLs() from Friedman et al. (1986) is added.
Now includes th
Dear Experts,
I have fitted MARS and GAM models on a real dataset. My goal is prediction. I
have run crossvalidation many times to get an idea of the out-of-bag accuracy
value. I use the Mean Squared Error (MSE) as an error evaluation criterion. I
have published my paper and the reviewers ask m
Hi,
Is there a label argument, please? I think that might be it.
In my example I had a label, but this not the problem since
> choices=list("choice1"=1, "choice2"=2,"choice3"=3)
> as.character(choices)
[1] "1" "2" "3"
delivers the result as it is used in sliderTextInput. I was hoping there
Here is a different approach that does not involve dplyr or the creation of
the intermediate data frame 'controls'
f <- function(v) {
any(v %in% c("E109","E119","E149")) & any(v %in% c("Caucasian")) &
any(v %in% c("No kinship found","Ten or more third-degree relatives
identified"))
}
tot$co
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