Hi,
The error message is explicit enough. You need 'y' for the paired test.
with(payoff, t.test(Open, Closed1, paired=TRUE))
HTH,
Pascal
On 25/03/13 07:42, Charlotte Rayner wrote:
This error keeps appearing when i perform a paired t-test in R
Error in t.test.default(payoff, paired = T) : '
Hi
Below is some code that does what I think you want by drawing a path
based on the map data. This does some grubby low-level work with the
'sp' objects that someone else may be able to tidy up
# The 21st polygon in 'hello' is the big outer boundary
# PLUS the 20 other inner holes
map <- a
This error keeps appearing when i perform a paired t-test in R
Error in t.test.default(payoff, paired = T) : 'y' is missing for paired test
This is the method i have used
> read.table("MeanPayoff.txt",header=T) Open Closed1 47.5 42.37502
> 49.25000 50.3 50.0 49.80004 33.5
I found the solution:
http://stats.stackexchange.com/questions/12993/how-to-setup-and-interpret-anova-contrasts-with-the-car-package-in-r
Sorry for the trouble.
On Sun, Mar 24, 2013 at 8:58 PM, Erin Hodgess wrote:
> Dear R People:
>
> I have the following in a file:
>
> resp factA factB
> 39.5
Dear R People:
I have the following in a file:
resp factA factB
39.5 low B-
38.6 high B-
27.2 low B+
24.6 high B+
43.1 low B-
39.5 high B-
23.2 low B+
24.2 high B+
45.2 low B-
33.0 high B-
24.8 low B+
22.2 high B+
and I construct the data frame:
> collard.df <- read.table("collard.txt",header=T
fitz_ra
> > I want to order the matrix using the second row in ascending order. From
> > the many examples (usually applied to columns) the typical solution
> > appears to be:
> >> temp[order(temp[2,]),]
> > Error: subscript out of bounds
That tries to reorder the rows of temp according the valu
or this with Pete's example
orig[,order(orig[2,])]
Pete Brecknock wrote
>
> fitz_ra wrote
>> I know this is posted a lot, I've been through about 40 messages reading
>> how to do this so let me apologize in advance because I can't get this
>> operation to work unlike the many examples shown.
sunny0 wrote
> I'd like to integrate vectors 't' and 'w' for log(w)/(1-t)^2 where i can
> vary the upper limit of the integral to change with each value of 't' and
> 'w', and then put the output into another vector.
>
> So, something like this...
>
> w=c(.33,.34,.56)
> t=c(.2,.5,.1)
> k-c(.3,.4,
fitz_ra wrote
> I know this is posted a lot, I've been through about 40 messages reading
> how to do this so let me apologize in advance because I can't get this
> operation to work unlike the many examples shown.
>
> I have a 2 row matrix
>> temp
>[,1] [,2] [,3] [,4] [,5]
Hello John,
Thank you so much for your kind assistance and the detailed descriptions.
I will play with the scripts and see which one is the easiest that serves
the purpose..
Best regards,
Janh
On Sun, Mar 24, 2013 at 7:50 AM, John Kane wrote:
> **
> Unless you have a really large number of we
your question doesn't seem to specifically related to either R or random
forest. instead, it is about how to assign weights to training
observations.
On Sun, Mar 24, 2013 at 6:43 AM, Lorenzo Isella wrote:
> Dear All,
> I am using randomForest to predict the final selling price of some items.
> A
Hi,
I am working on a GRASS script (bash script), which should run a R script.
I am working on Ubuntu 12.10, with R 2.15.3 and GRASS GIS 7.0 (I am not
sure the latter isn't really relevant as the grass script is just a bash
script). The R script is evoked with a call to Rscript ($RGRASSSCRIPT is a
On 3/24/2013 11:39 AM, Josh Hall wrote:
Hi,
I'm trying to create a boxplot from the summary of a large data set and I'm
having trouble finding any way to do this. I'm familiar with, but by no
means good at, using R, so the only two websites I've found pertaining to
this issue have been way over
Thanks you very much! Your help has been very useful!
Regards!
2013/3/23 mxkuhn
> train() in caret. See
>
>http://caret.r-forge.r-project.org/
>
> Also, the C5.0 function in the C50 is much more effective than J48.
>
> Max
>
> On Mar 23, 2013, at 2:57 PM, Nicolás Sánchez wrote:
>
> Good
Hi,
I'm trying to create a boxplot from the summary of a large data set and I'm
having trouble finding any way to do this. I'm familiar with, but by no
means good at, using R, so the only two websites I've found pertaining to
this issue have been way over my head. I was hoping for a simple set of
Yes, I think the second link is a test build of a parallelized cv loop within
gbm().
On Mar 24, 2013, at 9:28 AM, "Lorenzo Isella" wrote:
> Thanks a lot for the quick answer.
> However, from what I see, the parallelization affects only the
> cross-validation part in the gbm interface (but it
Thanks a lot for the quick answer.
However, from what I see, the parallelization affects only the
cross-validation part in the gbm interface (but it changes nothing when
you call gbm.fit).
Am I missing anything here?
Is there any fundamental reason why gbm.fit cannot be parallelized?
Lorenzo
Unless you have a really large number of wells I'd just use the brute force
approach of reading in each data set with a simple read.table or
read.csv like
well1 <- read.csv("well1.csv) type of statement and repeat for each well.
Here is a simple example that may give you an idea
See this:
https://code.google.com/p/gradientboostedmodels/issues/detail?id=3
and this:
https://code.google.com/p/gradientboostedmodels/source/browse/?name=parallel
Max
On Sun, Mar 24, 2013 at 7:31 AM, Lorenzo Isella wrote:
> Dear All,
> I am far from being a guru about parallel programm
Dear All,
I am far from being a guru about parallel programming.
Most of the time, I rely or randomForest for data mining large datasets.
I would like to give a try also to the gradient boosted methods in GBM,
but I have a need for parallelization.
I normally rely on gbm.fit for speed reasons, a
Dear All,
I am using randomForest to predict the final selling price of some items.
As it often happens, I have a lot of (noisy) historical data, but the
question is not so much about data cleaning.
The dataset for which I need to carry out some predictions are fairly
recent sales or even some
21 matches
Mail list logo
