Hi Dan,
Hi All,
many thanks for your help.
Please find enclosed my little function for your use:
-- cut --
#---
# Module: t_count_na.R
# Author: Georg Maubach
# Date : 2016-05-24
# Update
> ruipbarra...@sapo.pt
> Maybe the following (untested).
>
> table(df$Protocol[df$Speed == "SLOW"])
Could also use which.max to get the particular item: ...
tprot <- table(df$Protocol[df$Speed == "SLOW"])
tprot[which.max(tprot)]
S Ellison
*
Hi All,
Request your help.
We are trying to connect to hive from R using Rstudio. Its a kerberos secured
cluster. Code snippet is below.
==
library(rJava)
library(RJDBC)
cp =
c("/usr/hdp/2.3.2.0-2950/hive/lib/hive-jdbc.jar","/usr/hdp/2.3.2.0-2950/hadoop/lib/hadoop-common-2.7.1.2.
Dear R users,
I would like to announce a new package called "sparsevar" version 0.0.3:
https://cran.r-project.org/web/packages/sparsevar/
The package should be useful to estimate sparse VAR/VECM models.
The developing version can be found on Github:
https://github.com/svazzole/sparsevar
Best,
Reduce is failing when applied to a list of elements of class
data.table. Perhaps this is a bug?
Example:
library(data.table)
dt1 <- data.table(x = 1:3, y = 4:6)
dt2 <- data.table(x = 4:6, y = 1:3)
dt3 <- data.table(x = 0:-2, y = 0:-2)
# This works fine
dt1 + dt2 + dt2
#x y
# 1: 5 5
# 2:
Hi everyone,
I am searching for some toy models in R. My goal is do to model checking.
For example,
My data come from statistical model N(5, 2), with n=100, call this model_1
Then, I add bias to that data with N(3, 1), with n=100, call this model_2
Ultimately, I want to see model_1+ model_2 gi
This is a design feature of data.table objects, which don't conform to the
normal functional programming paradigm that R is usually designed to adhere to
and which Reduce expects. Specifically, they normally modify in-place rather
than leaving the original object alone.
In short, don't do that
> -Original Message-
> My data come from statistical model N(5, 2), with n=100, call this model_1
> Then, I add bias to that data with N(3, 1), with n=100, call this model_2
Do you mean you have data from N(5,2) that has had data from N(3,1) added to
it, or that you have two different sets
On Wed, May 25, 2016 at 1:13 PM, S Ellison wrote:
> > -Original Message-
> > My data come from statistical model N(5, 2), with n=100, call this
> model_1
> > Then, I add bias to that data with N(3, 1), with n=100, call this model_2
> Do you mean you have data from N(5,2) that has had data
Greetings R community,
My aim is to analyze a mixed-effects model with temporal pseudo-replication
(repeated measures on the same experimental unit) using ‘nlme’. However,
my code returns the error message “Error in na.fail.default’, even though
the data frame does not contain missing values. My
You forgot to show the commands to us that you used to read the data in with
(your example is not "reproducible"). This step can make all the difference in
the world as to whether your analysis commands will work or not.
--
Sent from my phone. Please excuse my brevity.
On May 25, 2016 11:59:06
Hello everyone,
almost every time I try to plot something R gives me the following mistake:
Error in plot.new() : figure margins too large
One example would be, when I tried to run a function, somebody published to
create a Lorenz Attractor:
parameters <- c(s = 10, r = 28, b = 8/3) state <- c(X
On 25/05/2016 12:56 PM, alicekalk...@freenet.de wrote:
Hello everyone,
almost every time I try to plot something R gives me the following mistake:
Error in plot.new() : figure margins too large
One example would be, when I tried to run a function, somebody published to
create a Lorenz Attractor:
It may not be the problem, but with RStudio this error pops up when
the area reserved for plotting is too small. Typically this area is in
the right hand column, if you have this minimised (perhaps to maximise
space for typing) you will hit this problem. Try making it bigger.
Edit: Just ran your c
Thanks for your attention. I have been using your R library, survey, I
made an example for two stage sampling SI – SI, an estimate the total and
the mean, (the point estimation y de SE)
and also, I remaking the estimation.
For the total, point estimation and estimation of the variance, we
Please keep the mailing list in the loop by using reply-all.
I don't think there is a requirement that the number of levels is equal, but
there may be problems if you don't have the minimum number of records
corresponding to each combination of levels specified in your model.
You can change th
I have a large dataset, a sample of which is:
a<- c(“A”, “B”,“A”, “B”,“A”, “B”,“A”, “B”,“A”, “B”)
b <-c(15, 35, 20, 99, 75, 64, 33, 78, 45, 20)
c<- c( 111, 234, 456, 876, 246, 662, 345, 480, 512, 179)
d<- c(1.1, 3.2, 14.2, 8.7, 12.5, 5.9, 8.3, 6.0, 2.9, 9.3)
df <- data.frame(a,b,c,d)
I’m tryin
Just to be clear, do you really want your 'condition' groups to be be
subsets
of one another? Most (all?) of the *ply functions assume you want
non-overlapping groups so they do a split-summarize-combine sequence.
You would have to replace the split part of that.
Bill Dunlap
TIBCO Software
wdunla
On Wed, 25 May 2016 18:56:47 +0200
alicekalk...@freenet.de wrote:
Alice,
Have you tried running the code in R in a terminal? If the error
persists, then this may be the right place to ask for help. If it is
specific to R Studio, then you need to ask them.
--
John
These will be overlapping subgroups from the same data frame. For example,
d<=2 will have length=9, d<=4 will have length=7, etc.
Ken
kmna...@gmail.com
914-450-0816 (tel)
347-730-4813 (fax)
> On May 25, 2016, at 9:06 PM, William Dunlap wrote:
>
> Just to be clear, do you really want your '
Hello, I just start using R. I want to use ??fitdistr?? to fit distribution of
the data. Then how can I verify if the data really fit the distribution? Thanks
[data is attached]
res<-fitdistr(data$Report.delay, "Poisson")
h<-hist(data$Report.delay)
xfit<-floor(seq(0, 250, 50))
yfit<-dp
Thank you for including some sample data, but I have to ask that you
please invest some time in learning how to edit your code in a text editor
and to post in plain text. The quote marks in your example were "curly",
which R does not understand. There are other ways in which HTML email
leads to
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