Not sure about JMP 11, but remember that JMP 10 did not run with R version >=
3.0.0
It depends a bit on the changes that come with new R versions; with JMP 10,
several versions of the 2.x series were compatible even though JMP officially
only supported earlier versions. I had hoped that with JM
I think R is doing exactly what you told it to do. Since you don't seem to be
satisfied, perhaps you need to explain what it is you want by giving us an
example of what you think you should end up with. You may have tried to do so,
but you failed to read and follow the Posting Guide (which warns
Hello everyone,
I have been trying to use the timedep(predictor) capability of the
frailtypack package in order to include time-varying covariates in a
frailty model. The following is an example of the code I use:
sha.time <- frailtyPenal(Surv(time,event)~cluster(id)+timedep(age)
,Frailty=TRU
Hi ,
I want to add a serialized data to a data frame . The representation does
not look good.
> x<- c(1,2)
> serialize(x,NULL)
[1] 58 0a 00 00 00 02 00 03 00 02 00 02 03 00 00 00 00 0e 00 00 00 02 3f f0
00
[26] 00 00 00 00 00 40 00 00 00 00 00 00 00
> y<-serialize(x,NULL)
> z=-1
> m<- data.frame(
Hi,
Does anyone have an example of a Markov Random Field smoother (MRF) in MGCV
where they have specified the neighbourhood directly, rather than supplying
polygons? Does anyone understand how the rules should be? Based on the
columb example, I have setup my data set and neighbourhood like so:
>
Hi Dustin,
Similar to what Boris suggested, try scaling the values and not
resetting the plot limits:
scaleBreak = function(x,y,axis=2,breakpos=1,ymult=0.45,...){
figure out which Y values are above the breakpos
y_above<-y[y>breakpos]
x_above<-x[y>breakpos]
y_below<-y[y<=bre
On closer inspection, change n=5 to n=10 in
major.ticks <- pretty(lims,n=5)
Then, I get 10^0, 10^1, etc. with all the minors. Is this what you want?
David
On 5/7/2014 10:32 AM, Shane Carey wrote:
Hey,
Im using the function below to create minor tick marks on log scale. It
only plots every se
Shane
I ran your code with debugging and found this for minor ticks
[1]> minor.ticks
[1] 1.00 1.301030 1.477121 1.602060 1.698970 1.778151 1.845098
1.903090 1.954243 3.00 3.301030
[12] 3.477121 3.602060 3.698970 3.778151 3.845098 3.903090 3.954243
5.00 5.301030 5.477121 5.602060
[
Thanks for the quick replies from Richard Heiberger, Greg Show &
Bert Gunter.
Might it make sense to create as.character.call as an alias for
deparse?
A few years ago, I wrote several functions like "predict.fd" as
aliases for functions with less memorable names like "eva
I'm a beginning R user.
The data: Volume of nectar in flowers under 4 different treatments, nested
for individual (measures were taken mutliple times from different flowers of
the same individual- never the same flower).
Specs: 54% of the data = 0. Variance=3.89. Mean=1.03. Sample size per
trea
... and
> str(quote(x$y))
language x$y
> as.list(quote(x$y))
[[1]]
`$`
[[2]]
x
[[3]]
y
## may be instructive.
Cheers,
Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
H. Gi
Google suggests that that error message is usually associated with cell phone
browsers, so what exactly are you doing (all steps, including browser info)? I
doubt that this an issue with R as such, more likely you have a general issue
with large downloads.
- Peter D
On 07 May 2014, at 19:37 ,
> deparse(quote(x$y))
[1] "x$y"
It looks like deparse does what you want here.
On Wed, May 7, 2014 at 3:23 PM, Spencer Graves
wrote:
> Hello, All:
>
>
> Is there a simple utility someplace to convert "quote(x$y)" to "x$y"?
>
>
> I ask, because as.character(quote(x$y)) is a character
> deparse(quote(x$y))
[1] "x$y"
On Wed, May 7, 2014 at 5:23 PM, Spencer Graves
wrote:
> Hello, All:
>
>
> Is there a simple utility someplace to convert "quote(x$y)" to "x$y"?
>
>
> I ask, because as.character(quote(x$y)) is a character vector of
> length 3 = "$" "x" "y". I want to
Hello, All:
Is there a simple utility someplace to convert "quote(x$y)" to
"x$y"?
I ask, because as.character(quote(x$y)) is a character vector of
length 3 = "$" "x" "y". I want to convert this to "x$y" for a
diagnostic message.
class(quote(x$y)) = "call", which sugg
https://communities.sas.com/message/199936
see link. Looks like R 3.1 may not yet be supported with JMP 11.
_
From: Robert Douglas Kinley
Sent: Wednesday, May 07, 2014 12:18 PM
To: r-help@r-project.org
Cc: Samuel J Gardner
Subject: R / JMP interface
Dear R-Help volunteers,
I received this error message when I tried to install R on my laptop: "The page
is too large to send back." The laptop has Windows 8, x64, enough memory space,
and open access (I have administrative rights). I have installed SPSS and SQL
but have never installed R. I tri
Revolution Analytics staff write about R every weekday at the Revolutions blog:
http://blog.revolutionanalytics.com
and every month I post a summary of articles from the previous month
of particular interest to readers of r-help.
In case you missed them, here are some articles related to R from t
Since points() and lines() plot on the scale of the last plot, you could plot
your "first" graph after the "second" one, or if there is a particular reason
why you plot them in the order you do, add a third, empty graph with the scale
of the first one as the last plot.
B.
On 2014-05-07, at
Hi,
In my work, I often investigate relationships between highly skewed data.
Example:
set.seed(111)
require(MASS)
d = data.frame(mvrnorm(1000, mu=c(0,0), Sigma=matrix(c(1,.6,.6,1), nrow=2)))
names(d) = c("x","y")
## Skew Y
d$y = d$y^4
plot(d$x, d$y)
lines(lowess(d$x, d$y), lwd=2, col="blue")
Un
On 07/05/2014 12:18 PM, Robert Douglas Kinley wrote:
hi useRs
I am trying-out the facility to call R code from JMP.
details: R 3.1.0 , JMP 11.1.1 , Windows 7 enterprise , all 64 bit.
The test-script from the JMP help pages falls over at the first line :-
R Init();
giving the error-message :-
The Predict.Plot function in the TeachingDemos package can do this for
you. Or you can just calculate the intercept for the call to abline
by plugging in the mean for all the other variables and do the
arithmetic then pass the intercept and slope by hand to the abline
function. Or you can create
Wov, so SAS/JMP has an interface to R. I'm amazed and it looks like SAS is
taking the "competition" from R seriously.
I'll check it out.
Frede
Sendt fra Samsung mobil
Oprindelig meddelelse
Fra: Robert Douglas Kinley
Dato:07/05/2014 18.19 (GMT+01:00)
Til: r-help@r-project.or
I'm looking for well-commented versions of various functions comprising
mgcv,
Commented versions are available e.g. in mgcv_*.*-**.tar.gz from CRAN
(unzip and look in mgcv/R). Well commented versions is another matter...
best,
Simon
--
Simon Wood, Mathematical Science, University of Bath BA2
Hey,
Im using the function below to create minor tick marks on log scale. It
only plots every second marker, i.e. 10^0, 10^2 and so on. How do I get it
to plot at every interval? Thanks
minor.ticks.axis <- function(ax,n,t.ratio=0.5,mn,mx,...){
lims <- par("usr")
if(ax %in%c(1,3)) lims <- lim
hi useRs
I am trying-out the facility to call R code from JMP.
details: R 3.1.0 , JMP 11.1.1 , Windows 7 enterprise , all 64 bit.
The test-script from the JMP help pages falls over at the first line :-
R Init();
giving the error-message :-
The installed version of R cannot be used. The entry
Oops.
> (ii) Your distance calculation is not the cartesian distance. That would be:
> sqrt(rowSums(iris2[1,]^2 - centers[1,]^2)).
Strike that. Need more coffee
:-O
> On 2014-05-07, at 4:34 AM, marioger wrote:
>
>> Hi,
>>
>> i am hoping you can help me with my problem. I am trying to
On May 7, 2014, at 5:15 AM, Abhinaba Roy wrote:
> Hi R-helpers,
>
> sumx <- summary(mtcars[,c("mpg","disp")])
>> sumx
> mpg disp
> Min. :10.40 Min. : 71.1
> 1st Qu.:15.43 1st Qu.:120.8
> Median :19.20 Median :196.3
> Mean :20.09 Mean :230.7
> 3rd Qu.:22.80 3rd
Three comments:
(i)If you calculate distances like this, you are weighting all columns
equally by absolute numbers. Depending on your application, you might
want to normalize the columns first (and before clustering).
(ii) Your distance calculation is not the cartesian distance
Try replacing your order() call with the following 2 lines
meanClusterRadius <- ave(distances, kmeans.result$cluster, FUN = mean)
outliers <- order(distances/meanClusterRadius, decreasing = T)[1:5]
ave(x,group,FUN=fun) applies FUN to the subsets of x defined by the
group argument(s) and pu
Hello,
thanks a lot for the fast response and the hint! Actually, it helped to
already integrate as.factor in the generation of the raster. This is
also working for uploading or diverse other raster functionalities like
projection, e.g. as.factor(raster("C:\\...\\r.tiff")) or
as.factor(projec
Hi,
i am hoping you can help me with my problem. I am trying to detect outliers
with use of the kmeans algorithm. First I perform the algorithm and choose
those object as possible outliers which have a big distance to their cluster
center. Instead of using the absolute distance I want to use the r
Hi R-helpers,
sumx <- summary(mtcars[,c("mpg","disp")])
> sumx
mpg disp
Min. :10.40 Min. : 71.1
1st Qu.:15.43 1st Qu.:120.8
Median :19.20 Median :196.3
Mean :20.09 Mean :230.7
3rd Qu.:22.80 3rd Qu.:326.0
Max. :33.90 Max. :472.0
I want a dataframe as
Ok, an extra blank space at the end was the problem. I missed it.
Cheers,
2014-05-07 9:05 GMT-03:00 Alejo C.S. :
> Hi all, I have a data frame with names that in some cases have blank
> spaces:
>
> > TABLE$place
> [1] La Blanqueada La Blanqueada La Blanqueada La Blanqueada La
> Blanquead
Hi all, I have a data frame with names that in some cases have blank spaces:
> TABLE$place
[1] La Blanqueada La Blanqueada La Blanqueada La Blanqueada La
Blanqueada
[6] La Blanqueada La Blanqueada Sargento Ponce Sargento Ponce La
Blanqueada
[11] La Blanqueada Sargento Ponce La Blanqueada
Dear all,
I use R 3.0.2 for Windows 7.
I performed a sub-groups meta-analysis of the prevalence (single
proportion)reported in 14 different studies using the package meta
(April 19, 2014). I have two groups.
I use the line commands:
res <-metaprop(case,n,sm="PFT", comb.fixed=FALSE, comb.rando
Brilliant - thanks very much for your help!
Tom
On 6 May 2014 23:08, David Winsemius wrote:
>
> On May 6, 2014, at 2:51 PM, Tom Walker wrote:
>
>> Hi,
>>
>> I need to generate bar charts where the x-axis is a factor that
>> includes a mixture of species names (in italic) and control treatments
>
Mia Bengtsson gmail.com> writes:
>
> Dear R and vegan package users,
>
> I have been experiencing problems with the metaMDS function when working
on a dataset (euk) consisting of 9
> "sites" (RNA extracts of 9 biofilms samples) and 340 "species" (microbial
taxa based on rRNA sequences).
> The p
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