-Original Message-
From: r-sig-debian-boun...@r-project.org [mailto:r-sig-debian-bounces@r-
project.org] On Behalf Of Ajay Ohri
Sent: Friday, January 21, 2011 10:50 PM
To: r-sig-deb...@r-project.org; R list
Subject: [R-sig-Debian] Debian ?Ubuntu version of latest R using synaptic
Any advice on which package I can use for calculating effect sizes for two
dependent samples? compute.es seems only to consider independent samples.
Thanks in advance
Steve Powell
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On Fri, Jan 21, 2011 at 10:10 PM, Mingo catojo...@gmail.com wrote:
Hello, I am new to R (coming from Perl) and have what is, at least at this
point, a philosophical question and a request for comment on some basic
code. As I understand it - R emphasizes ,or at least supports, the
functional
Ajay
Please avoid cross-posting on two lists. Continue this thread only on
thes-ig-debian list.
You can't update packages from within R? Did you try to start R with
sudo permissions?:
sudo R
Hope this helps
Mat
Le 22. 01. 11 07:50, Ajay Ohri a écrit :
Dear List
I use synaptic to
Dear R community
Recently, dear Henrique Dallazuanna literally saved me solving one
problem on data transformation which follows:
(n_, _n, j_, k_ signify numbers)
SOURCE DATA:
id cycle1 cycle2 cycle3 … cycle_n
1 c c c c
1 m m m
...One more important thing:
After updating your packages with sudo
if you have additional packages installed with
'install.packages(name, dependencies=TRUE)' in R
you will have to reinstall them
Regards
Denis
У Суб, 22/01/2011 у 12:20 +0530, Ajay Ohri піша:
Dear List
I use synaptic to
Hello everybody,
I have a problem that is bothering me for quite a while now and I
don't know the answer... I want to create global variables (out of a
function) which I can access from all other functions... But somehow
that does not work too well. Attached some code for an example:
Dear all,
I am looking for an equivalent to the newey2-extension in Stata, in
order to compute Newey-West HAC standard errors in a regression using
panel data.
I would be very grateful for advice which R-package could do this.
I thank you very much in advance.
Dirius
Hello everyone,
I came cross a question when trying to use the cluster and clv package.
For validation, offen there is a parameter named 'clust', which is an
integer vector with information about cluster id.
If I have my own clustering result, and I'd like to read it from a file by
R, what the
Ajay,
you may try to run R as root while updating packages. Some
packages insist to install in directories writeable only by root.
On Saturday 22 January 2011 07:50:10 Ajay Ohri wrote:
Dear List
I use synaptic to download R on my Ubuntu 10.10. It seems latest version of
R on Ubuntu is
Hello,
does anybody know another faster function for random multivariate normal
variable simulation? I'm using mvrnorm, but as profiling shows, my algorithm
spends approximately 50 % in executing mvrnorm function.
Maybe some of you knows much faster function for multivariate normal
simulation?
I
On Sat, Jan 22, 2011 at 12:13:35PM +0530, pratik wankhade wrote:
I have a problem as follows:
1. If we have 3 matrices A,B,C and we merge them in a single matrix ABC by
any method like addition , subtraction division,multiplication,etc
2. and then we want to retrieve original 3 matrices
On 11-01-22 3:06 AM, Lui ## wrote:
Hello everybody,
I have a problem that is bothering me for quite a while now and I
don't know the answer... I want to create global variables (out of a
function) which I can access from all other functions... But somehow
that does not work too well. Attached
Dear R Fans,
I have the opportunity to buy a new computer for my simulations in R. My
goal is to get the execution of R code as fast as possible. I know that
the number of cores and the working memory capacity are crucial for
computer performance but maybe someone has experience/knowledge
(1)
a = c(a,b)
mode(a)
[1] character
b = c(1,2)
mode(b)
[1] numeric
c = data.frame(a,b)
mode(c$a)
[1] numeric
(2)
a = c(a,a,b,b,c)
levels(as.factor(a))
[1] a b c
levels(as.factor(a[1:3]))
[1] a b
a = as.factor(a)
levels(a)
[1] a b c
levels(a[1:3])
[1] a b c
Any explanation would
(1)
a - c(a, b)
str(a)
chr [1:2] a b
b - c(1,2)
str(b)
num [1:2] 1 2
c - data.frame(a, b)
str(c)
'data.frame': 2 obs. of 2 variables:
$ a: Factor w/ 2 levels a,b: 1 2
$ b: num 1 2
mode(c$a)
[1] numeric
c2 - data.frame(a, b, stringsAsFactors=FALSE)
str(c2)
'data.frame': 2 obs.
On Sat, 22 Jan 2011 06:16:43 -0800 (PST)
analys...@hotmail.com analys...@hotmail.com wrote:
(1)
a = c(a,b)
mode(a)
[1] character
b = c(1,2)
mode(b)
[1] numeric
c = data.frame(a,b)
mode(c$a)
[1] numeric
R str(c)
'data.frame': 2 obs. of 2 variables:
$ a: Factor w/ 2 levels
On 11-01-22 14:56, Marc Jekel wrote:
I have the opportunity to buy a new computer for my simulations in R. My goal
is to get the execution of R code as fast as possible. I know that the number
of cores and the working memory capacity are crucial for computer performance
but maybe someone has
My explanation for No2:
When coercing a character vector to factor, the current levels are stored.
By choosing a subvector of the factor you don't change the levels of the
factor. So levels(a[1:3]) is still [1] a b c in the last line ...
If you want to reduce levels you need to tell R.
On Sat, 22 Jan 2011, Dirk Heine wrote:
Dear all,
I am looking for an equivalent to the newey2-extension in Stata, in
order to compute Newey-West HAC standard errors in a regression using
panel data.
I would be very grateful for advice which R-package could do this.
I wouldn't be aware of
Please read the posting guide to learn how to ask a coherent question
(at least to me; maybe others will get it).
-- Bert
On Sat, Jan 22, 2011 at 1:55 AM, Steve Powell st...@promente.net wrote:
Any advice on which package I can use for calculating effect sizes for two
dependent samples?
On Jan 22, 9:50 am, Berwin A Turlach ber...@maths.uwa.edu.au wrote:
On Sat, 22 Jan 2011 06:16:43 -0800 (PST)
analys...@hotmail.com analys...@hotmail.com wrote:
(1)
a = c(a,b)
mode(a)
[1] character
b = c(1,2)
mode(b)
[1] numeric
c = data.frame(a,b)
mode(c$a)
[1]
I must get an index (fuzzy silhouette), a weighted average. A average the
crisp silhouette for every row (i) s and the weight of each term is
determined by the difference between the membership degrees of corrisponding
object to its first and second best matching fuzzy clusters.
i need the
On Jan 22, 2011, at 10:03 AM, Sascha Vieweg wrote:
On 11-01-22 14:56, Marc Jekel wrote:
I have the opportunity to buy a new computer for my simulations in
R. My goal is to get the execution of R code as fast as possible. I
know that the number of cores and the working memory capacity are
Den wrote:
Dear R community
Recently, dear Henrique Dallazuanna literally saved me solving one
problem on data transformation which follows:
(n_, _n, j_, k_ signify numbers)
SOURCE DATA:
id cycle1 cycle2 cycle3 … cycle_n
1 c c c c
1 m
On 11-01-20 17:05, Sascha Vieweg wrote:
I run a multinomial regression on a data set with an outcome that has three
values. First, I build an initial model, b.mod. Then I run a loop to
bootstrap the coefficients. For the initial model, using predict(), I can
print the wrong/false predictions
fantomas tomas.iesmantas at gmail.com writes:
Hello,
does anybody know another faster function for random multivariate normal
variable simulation? I'm using mvrnorm, but as profiling shows, my algorithm
spends approximately 50 % in executing mvrnorm function.
Maybe some of you knows
Hi all,
I've got an xts time series of stock symbols and closing prices.
head(x)
symbol close
2010-01-04 AFB 13.46
2010-01-04 AKP 12.80
2010-01-04 APX 8.78
2010-01-04 AYN 13.15
2010-01-04 BAF 13.50
2010-01-04 BBF 12.86
tail(x)
symbol close
2011-01-21 VMO 12.35
Hello. Thx Achim for forwarding.
Although simple Newey-West is feasible in panels, the best panel analogue is
perhaps Driscoll and Kraay's SCC covariance estimator, which extends
Newey-West allowing for (contemporaneous and lagged-) cross-sectional as well
as serial correlation.
This is
If you type ?as.data.frame and ?data.frame you can see there are
differences. data.frame() can take more than one data parameter.
#producing different results:
data.frame(c(1,2,3), c(hello,world,!))
as.data.frame(c(1,2,3), c(hello,world,!))
there are differences (in parameters) for as.factor
Hi All,
Trying to figure out the way to create a vector of values inside a loop
I have a matrix pop:
Id yloc xloc weight
1
2
.
and spatial grid grid.dens with coordinates (x=xloc,y=yloc)
I want to create two more vectors: Food and Consumed inside the loop and
add those to pop so:
Id
On Sat, Jan 22, 2011 at 8:17 AM, Duncan Murdoch
murdoch.dun...@gmail.com wrote:
On 11-01-22 3:06 AM, Lui ## wrote:
Hello everybody,
I have a problem that is bothering me for quite a while now and I
don't know the answer... I want to create global variables (out of a
function) which I can
Greetings all,
I am wondering if anyone is aware of any studies that draw a
relationship between an actor and their box office gross for a movie.
In other words, is anybody aware of any databases that contain box
office movie grosses, actor director info., advertising budget, etc,
etc. [ I did a
Please unsubscribe me from r-help as I am having trouble from unsubscribing
myself.
mgog...@gmail.com
Thanks,
mgogos
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PLEASE
Kamel,
You have already had several comments suggesting some ideas for improvement,
namely,
1) correct name for iteration limit (Karl Ove Hufthammer)
2) concern about number of parameters and also possibilities of multiple minima
(Doug Bates)
3) use of optimx to allow several optimizers to be
Hi to all R community
Does anybody know good R packages/books dedicated to efficient usage of
R in pharmacoepidemiological research?
Thank you in advance
--
Denis Kazakiewicz d.kazakiew...@gmail.com
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Dear All,
I want to use grofit package for biological growth curves. My dataset only
includes age variable and size variable. I want to use logistic, gompertz
and richards growth curves to predict age from size. How can I implement this
data set to the function in grofit package?
Best
hi
i have one table sireall.txt
SNP1 SNP2 SNP3 SNP4 SNP5 SIRE1 1 -1 -1 1 -1 SIRE2 1 -1 1 1 1 SIRE3 -1
-1 1 1 0 SIRE4 -1 1 1 0 1 SIRE5 -1 1 -1 -1 1 SIRE6 0 0 0 1 -1 SIRE7 -1 0
-1 1 1 SIRE8 1 -1 NA 0 NA SIRE9 -1 1 1 -1 -1 SIRE10 1 1 1 1 1
SIRE100 1 1 -1 1 1
[[alternative
Hi
ihave one table that look like
SNP1 SNP2 SNP3 SNP4 SNP5
SIRE1 1 -1 -1 1 -1
SIRE2 1 -1 1 1 1
SIRE3 -1 -1 1 1 0
SIRE4 -1 1 1 0 1
SIRE5 -1 1 -1 -1 1
SIRE6 0 0 0 1 -1
SIRE7 -1 0 -1 1 1
SIRE8 1 -1 NA 0 NA
SIRE9 -1 1 1 -1 -1
Hi
I am attempting to use plotLMER.fnc
from the languageR library to plot
partial effects of models fited with lmer.
This appears to be straightforward for some of my models,
e.g:
mod-lmer(NoBranches~PCA1+SP+(1|ProvCode)+(1|SoilZone),REML=FALSE,data=treedata1)
plotLMER.fnc(mod)
Hello,
Is the std.dev component of ls.diag( lsfit(x,y) ) the sample standard
deviation of the residuals of the fit?
I have
ls.diag(lsfit(xx,yy))$std.dev
different from
sd(lsfit(xx,yy)$residuals)
where xx and yy are vectors of 5 elements.
Regards,
Hi,
Yes, that is basically the idea. It is defined as:
stddev - (colSums(as.matrix(resids^2))/(n - p))^0.5
Where n is the number of rows in the residual matrix and p is the rank
of the QR decomposition. I believe the reason they are slightly
different is that the mean of the residuals is not
Greetings!
Is there in any package for R which can help me generate madogram, rodogram,
semi-variogram, cross variogram from landsat imagery. I intend to select
portions of large imagery (i.e., obtain subsets) and generate the above said
texture layers. A simple Google search led to me a result
So I've got a 154 column wide xts time series object and I want to plot the
154 series on a single plot and have the added benefit of the time series
dates on the x axis.
Any suggestions for plotting functions, maplot works but does not give dates
on the axis and I can't seem to get plot to give
See ?plot.zoo, specifically plot.type=single.
--
Joshua Ulrich | FOSS Trading: www.fosstrading.com
On Sat, Jan 22, 2011 at 8:02 PM, Nick Torenvliet
nick.torenvl...@gmail.com wrote:
So I've got a 154 column wide xts time series object and I want to plot the
154 series on a single plot and
Hi:
is there a difference between the as.factor and factor commands
and also between as.data.frame and data.frame?
The as.* construct coerces an object from one class to another, so
as.factor() can be used to, for example, coerce a character string to a
factor object. The factor() function is
Hi Marc,
I've exactly the same question and it looks like most of the heavy users
from the threads I've followed use Unix/Linux/Mac.
Some threads have given rationale for a 64bit system due to memory benefits
but there seems to be not much buy-in from the guys here (so I'd give that a
pass). The
On Sat, Jan 22, 2011 at 6:37 PM, Santosh Srinivas
santosh.srini...@gmail.com wrote:
Hi Marc,
I've exactly the same question and it looks like most of the heavy users
from the threads I've followed use Unix/Linux/Mac.
Some threads have given rationale for a 64bit system due to memory benefits
On Sat, Jan 22, 2011 at 12:46 PM, Nick Torenvliet
nick.torenvl...@gmail.com wrote:
Hi all,
I've got an xts time series of stock symbols and closing prices.
head(x)
symbol close
2010-01-04 AFB 13.46
2010-01-04 AKP 12.80
2010-01-04 APX 8.78
2010-01-04 AYN 13.15
2010-01-04
Hi Josh,
I was referring to the below point that I read a while back when I
installed my first R (didn't mean to imply that 64 bit was not
needed). Some packages also had issues on 64bit (I think I ran into
some with RQuantLib). Maybe this could be worked around if there is
enough time. The
Dear All.
I have some problem with combined two data frame.
I have first data frame ..
GPAX THAI MATH SCINCE SOCIAL HEALT ART CAREER LANGUAGE
1227 2.99 3.32 2.50 2.64 3.05 3.60 3.72 3.57 2.62
1704 2.81 2.56 2.48 2.86 3.22 3.19 3.55 3.20 2.51
617 2.18 1.90 1.97
Hi
So let's call first data frame df1 and second df2
#replace NA with 2.36
df2y - lapply(df2, function(x) (ifelse( is.na(x), 2.36,x)))
#combibe
both - rbind(df1, df2)
With best regards
Denis
У Няд, 23/01/2011 у 12:41 +0700, Jumlong Vongprasert піша:
Dear All.
I have some problem with
Dear Dennis
Thank you very much for your comprehensive reply and for time you've
spent dealing with my e-mail.
Your kindly explanation made things clearer for me.
After your explanation it looks simple.
lapply with chosen options takes small part of cyclen with same id
(eg. df[df$id==3,cycle2]
Hi
ihave one table that look like
SNP1 SNP2 SNP3 SNP4 SNP5
SIRE1 1 -1 -1 1 -1
SIRE2 1 -1 1 1 1
SIRE3 -1 -1 1 1 0
SIRE4 -1 1 1 0 1
SIRE5 -1 1 -1 -1 1
SIRE6 0 0 0 1 -1
SIRE7 -1 0 -1 1 1
SIRE8 1 -1 NA 0 NA
SIRE9 -1 1 1 -1 -1
SIRE10 1 1 1 1 1
Hi:
If you mean how to tack on table 2 to the bottom of table 1, then
rbind(table1, table2)
should do it. If you mean something else, perhaps you should clarify what
you mean by
'table1 * table2'.
HTH,
Dennis
On Sat, Jan 22, 2011 at 10:00 PM, shai uliel ulie...@gmail.com wrote:
Hi
ihave
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