Dear Ivan,
Thanks a lot.!
Thanking you,
Yours sincerely,
AKSHAY M KULKARNI
From: Ivan Krylov
Sent: Saturday, December 24, 2022 9:27 PM
To: akshay kulkarni
Cc: R help Mailing list
Subject: Re: [R] difference between script and a function
On Sat, 24 Dec 2022 15:47:14 +
akshay kulkarni wrote:
> How do you debug if there is an error, particularly if I run the
> script from the BASH prompt?
Post-mortem debugging for non-interactive R scripts can be enabled by
setting options(error = quote(dump.frames("A_SUITABLE_FILE_NAME",
...but from the
Linux prompt?
Thanking you,
Yours sincerely,
AKSHAY M KULKARNI
From: Ivan Krylov
Sent: Saturday, December 24, 2022 8:52 PM
To: akshay kulkarni
Cc: R help Mailing list
Subject: Re: [R] difference between script and a function
On Sat, 24 Dec 2022 14:54
On Sat, 24 Dec 2022 14:54:52 +
akshay kulkarni wrote:
> If there is some error in the script, the error will be output to
> the stdout? Or to the file that it creates for saving the output of
> the script?
When using Rscript: to stderr, to be precise.
When using R CMD BATCH: to the Rout
From: Andrew Simmons
Sent: Saturday, December 24, 2022 8:18 PM
To: akshay kulkarni
Cc: R help Mailing list
Subject: Re: [R] difference between script and a function
1. The execution environment for a script is the global environment. Each R
script run from a shell
1. The execution environment for a script is the global environment. Each R
script run from a shell will be given its own global environment. Each R
session has exactly one global environment, but you can have several active
R sessions.
2. Using return in a script instead of a function will throw
Dear members,
I will be running scripts automatically in RHEL
with crontab. I want to know the differences between running a script and a
function. in particular:
1. An execution environment will be created for the function. what about a
script? Is the
Hello,
I would like to know the diffrence between 2 commands : cor_auto (from qgraph
package) and lavCor (from lavaan package) to compute a polychoric correlation
matrix in order to do a network analysis.
I have the responses to the SF-36 questionnaire (36 items with ordered
responses) and I
Because ifelse is not intended to be an alternative to if ... else. They exist
for different purposes.
(besides the other replies, a careful reading of their help pages, and trying
the examples, should explain the different purposes).
--
Don MacQueen
Lawrence Livermore National Laboratory
7000
On 13/12/2017 10:31 AM, Jinsong Zhao wrote:
Hi there,
I don't know why the following codes are return different results.
> ifelse(3 > 2, 1:3, length(1:3))
[1] 1
> if (3 > 2) 1:3 else length(1:3)
[1] 1 2 3
Any hints?
The documentation in the help page ?ifelse and ?"if" explains it pretty
ifelse returns the "shape" of the first argument
In your ifelse the shape of "3 > 2" is a vector of length one, so it will
return a vector length one.
Avoid "ifelse" until you are very comfortable with it. It can often burn
you.
On Wed, Dec 13, 2017 at 5:33 PM, jeremiah rounds
ifelse is vectorized.
On Wed, Dec 13, 2017 at 7:31 AM, Jinsong Zhao wrote:
> Hi there,
>
> I don't know why the following codes are return different results.
>
> > ifelse(3 > 2, 1:3, length(1:3))
> [1] 1
> > if (3 > 2) 1:3 else length(1:3)
> [1] 1 2 3
>
> Any hints?
>
> Best,
>
Hi there,
I don't know why the following codes are return different results.
> ifelse(3 > 2, 1:3, length(1:3))
[1] 1
> if (3 > 2) 1:3 else length(1:3)
[1] 1 2 3
Any hints?
Best,
Jinsong
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and
Well,...
cat() is as Jeff describes.
However, print() is a generic function (see ?UseMethod) for which
there are literally hundreds of different methods that may do far
more/different than merely output character strings. For example, the
print method for trellis objects, print.trellis, draws a
Please stop posting html email per the Posting Guide. You are only going to
reduce the chance of successfully communicating your questions to experienced
users on this list.
Re cat vs print: the purpose of print is to show values much as they are
entered in source code, so quotes and escaped
Since both *cat * as well as * print * create a character vector for
outputing on the screen. Still both give different results as apparant
below. My query is why so ?
> cat(10)
10
> print(10)
[1] 10
Why is the [1] of index number missing in case of *cat *?
Thanks
Ramnik
[[alternative
[This is drifting somewhat awy from the original intention of the topic, I
think].
This looks like a build dependency. I get
3.3.2 (yeah, I know, should upgrade):
> (1+2i)/0
[1] NaN+NaNi
R-devel, march 24:
> (1+2i)/0
[1] Inf+Infi
on the *same* machine. The difference is that one is stock
> On 31 Mar 2017, at 19:28, John McKown wrote:
>
> On Fri, Mar 31, 2017 at 12:15 PM, Berend Hasselman wrote:
>
> I have noted a difference between R on macOS en on Kubuntu Trusty (64bits)
> with complex division.
> I don't know what would happen
On Fri, Mar 31, 2017 at 12:15 PM, Berend Hasselman wrote:
>
> I have noted a difference between R on macOS en on Kubuntu Trusty (64bits)
> with complex division.
> I don't know what would happen R on Windows.
>
> R.3.3.3:
>
> macOS (10.11.6)
> -
> > (1+2i)/0
> [1]
On 31.03.2017 19:15, Berend Hasselman wrote:
I have noted a difference between R on macOS en on Kubuntu Trusty (64bits) with
complex division.
I don't know what would happen R on Windows.
R.3.3.3:
macOS (10.11.6)
-
(1+2i)/0
[1] NaN+NaNi
(-1+2i)/0
[1] NaN+NaNi
1i/0
I have noted a difference between R on macOS en on Kubuntu Trusty (64bits) with
complex division.
I don't know what would happen R on Windows.
R.3.3.3:
macOS (10.11.6)
-
> (1+2i)/0
[1] NaN+NaNi
> (-1+2i)/0
[1] NaN+NaNi
>
> 1i/0
[1] NaN+NaNi
> 1i/(0+0i)
[1] NaN+NaNi
The only place I've noticed differences is in encoding and string sorting,
both of which are locale and library dependent.
Best,
Ista
On Mar 31, 2017 8:14 AM, "Neil Salkind" wrote:
> Can someone please direct me to an answer to the question as to how R
> differs for
File encodings differ when you move outside of standard ASCII code. Not really
R's problem, but it is a fly in the ointment when teaching classes with mixed
laptop armoury and there are also differences between classroom and desktop
computers. RStudio does have features to switch encodings, but
> On Mar 30, 2017, at 8:40 PM, Boris Steipe wrote:
>
> I can't remember having seen my students write code that runs correctly on
> one platform but not the other. Obviously under the hood there are
> significant differences, but as far as code goes, R seems quite
I can't remember having seen my students write code that runs correctly on one
platform but not the other. Obviously under the hood there are significant
differences, but as far as code goes, R seems quite foolproof. There are GUI
differences in base R - but AFAIK no such differences in the
Can someone please direct me to an answer to the question as to how R differs
for these two operating systems, if at all? Thanks - Neil
__
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https://stat.ethz.ch/mailman/listinfo/r-help
Dear Jean,
Have a look at
http://stackoverflow.com/questions/5595512/what-is-the-difference-between-require-and-library
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics &
Hi,
Is there any other difference between 'require' and 'library' than the error or
warning when the library is not found ?
Jean in France
Ce message et toutes les pièces jointes (ci-après le 'Message') sont établis à
l'intention exclusive des destinataires et les informations qui y
Hi catalin,
I think what you are trying to do is to retrieve the original
observations from the cumulated values. In that case Olivier's
suggestion will do what you want:
c(x[1],diff(x))
Jim
On Sat, Mar 5, 2016 at 1:59 AM, catalin roibu wrote:
> I mean the first row
I mean the first row value
În Vin, 4 mar. 2016, 16:15 Jeff Newmiller, a
scris:
> "Keep the first values" is imprecise, but mixing an absolute value with a
> bunch of differences doesn't usually work out well. I frequently choose
> among
>
> x <- sample( 10 )
> dxright
"Keep the first values" is imprecise, but mixing an absolute value with a bunch
of differences doesn't usually work out well. I frequently choose among
x <- sample( 10 )
dxright <- c( 0, diff(x) )
dxleft <- c( diff(x), 0 )
for calculation purposes depending on my needs.
--
Sent from my
Hi,
(1) You should provide a minimal working example;
(2) But anyway, does...
x = sample(10)
c(x[1],diff(x))
... do what you want?
Olivier.
On Fri, 4 Mar 2016
13:22:07 +0200 catalin roibu wrote:
> Dear all!
>
> I want to calculate difference between successive
Dear all!
I want to calculate difference between successive values (cumulative
values) with R. I used diff function, but I want to keep the first values.
Please help me to solve this problem!
Thank you!
Best regards!
CR
--
-
-
Catalin-Constantin ROIBU
Lecturer PhD, Forestry engineer
On 16-08-2015, at 16:38, Jinsong Zhao jsz...@yeah.net wrote:
Hi there,
I notice that write.csv is a wrap of write.table. However, I can't get the
same results using both functions. Here is a reproducible example:
x - matrix(1:6, nrow =2)
rownames(x) - letters[1:2]
colnames(x) -
On Aug 16, 2015, at 9:38 AM, Jinsong Zhao jsz...@yeah.net wrote:
Hi there,
I notice that write.csv is a wrap of write.table. However, I can't get the
same results using both functions. Here is a reproducible example:
x - matrix(1:6, nrow =2)
rownames(x) - letters[1:2]
colnames(x)
I think that if you do ?write.csv and then page down to the section
entitled CSV files the mystery will be solved for you in the first few
paragraphs.
On 16/08/2015 15:38, Jinsong Zhao wrote:
Hi there,
I notice that write.csv is a wrap of write.table. However, I can't get
the same results
Hi there,
I notice that write.csv is a wrap of write.table. However, I can't get
the same results using both functions. Here is a reproducible example:
x - matrix(1:6, nrow =2)
rownames(x) - letters[1:2]
colnames(x) - LETTERS[1:3]
write.csv(x, )
,A,B,C
a,1,3,5
b,2,4,6
write.table(x, ,
Dear list members,
I’m having some problems understanding why drop1() and anova() gives
different results for *Gaussian* glm models. Here’s a simple example:
d = data.frame(x=1:6,
group=factor(c(rep(A,2), rep(B, 4
l = glm(x~group, data=d)
Running the following code
I am somewhat surprised that _anything_ sensible comes out of anova.glm(l,
test=Chisq). I think it is mostly expected that you use F tests for that case.
What does seem to come out is the same as for drop1(l, test=Rao), which gives
the scaled score test, which would seem to be equivalent to
Dear Duncan,
I had been thinking about FAQ 7.31. I tried to create a dummy dataset with
the same structure to replicate the problem with the need of sending my
dataset. However all of them gave identical() results between 32-bit and
64-bit. Note that coef()$fRow is a 1266 x 6 data.frame. Is it
low probability of occurring was just statisticians lingo for rare ;-)
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie Kwaliteitszorg / team Biometrics Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
To call in
On 04/06/2015 3:59 AM, Thierry Onkelinx wrote:
Dear Duncan,
I had been thinking about FAQ 7.31. I tried to create a dummy dataset
with the same structure to replicate the problem with the need of
sending my dataset. However all of them gave identical() results between
32-bit and 64-bit.
On 03/06/2015 11:56 AM, Thierry Onkelinx wrote:
Dear all,
I'm a bit puzzled by the difference in an object when created in R 32-bit
and R 64-bit.
Consider the code below. test.rda is available at
https://drive.google.com/file/d/0BzBrlGSuB9n-NFBWeC1TR093Sms/view?usp=sharing
# Run in R
Dear all,
I'm a bit puzzled by the difference in an object when created in R 32-bit
and R 64-bit.
Consider the code below. test.rda is available at
https://drive.google.com/file/d/0BzBrlGSuB9n-NFBWeC1TR093Sms/view?usp=sharing
# Run in R 3.2.0 Windows 32-bit, lme4 1.1-8
library(lme4)
]
Sent: zaterdag 14 februari 2015 8:16
To: 'Martyn Byng'; r-help@r-project.org
Cc: Franckx Laurent
Subject: RE: [R] difference between max in summary table and max function
I thought I'd chime in ... submitting the following:
?summary
Provides the following documentation for the default
Dear all
I have found out that the max in the summary of an integer vector is not always
equal to the actual maximum of that vector. For example:
testrow - c(1:131509)
summary(testrow)
Min. 1st Qu. MedianMean 3rd Qu.Max.
1 32880 65760 65760 98630 131500
Its a formatting thing, try
summary(testrow,digits=20)
-Original Message-
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Franckx Laurent
Sent: 13 February 2015 11:00
To: r-help@r-project.org
Subject: [R] difference between max in summary table and max function
Dear all
Byng
Sent: Friday, February 13, 2015 3:15 AM
To: Franckx Laurent; r-help@r-project.org
Subject: Re: [R] difference between max in summary table and max function
Its a formatting thing, try
summary(testrow,digits=20)
-Original Message-
From: R-help [mailto:r-help-boun...@r-project.org
Dear R users and contributors,
I recently observed a difference between the outputs of the classic
eigen() function, and the Arnoldi variant eigs() that extracts only
the few first eigenpairs. Here is some sample code illustrating the
problem:
library(rARPACK)
library(speccalt)
set.seed(1)
#
eigs() is from a contributed package. No idea what it is about, but my
guess is these are actually numerical differences coming from different
algorithms used to calculate the eigenvalues.
For details, please ask the author of the corresponding contributed package.
Best,
Uwe Ligges
On
Hi,
It is better to show the example data using ?dput(). Here, it is not clear
whether the columns are character columns or lists.
##If it is the latter case
dat1 - data.frame(V1=I(list(1:3, c(1,2,4), c(2,3,4,5))), V2= I(list(c(3,6,5),
c(7,10,9), 2:5)))
dat1$V3 - mapply(`c`,mapply(`-`,
HI,
I guess this should be a bit faster.
#1st case
dat1$V3 - lapply(seq_along(dat1$V2),function(i) c(dat1$V2[[i]][-1] -
head(dat1$V1[[i]],-1), tail(dat1$V1[[i]],1)))
#2nd case
dat2$V3 - unlist(lapply(seq_along(lst1[,2]),function(i)
paste(c(lst1[,2][[i]][-1] - head(lst1[,1][[i]], -1),
On 18/04/2014 21:46, David Winsemius wrote:
On Apr 18, 2014, at 12:59 PM, Prof Brian Ripley wrote:
On 18/04/2014 19:46, Rui Barradas wrote:
Hello,
The reason why is that you've misspelled CET (not CEST)
Neither CET nor CEST are portable time-zone names. We have not been given the
'at a
On 20/04/2014 08:50, Prof Brian Ripley wrote:
On 18/04/2014 21:46, David Winsemius wrote:
On Apr 18, 2014, at 12:59 PM, Prof Brian Ripley wrote:
On 18/04/2014 19:46, Rui Barradas wrote:
Hello,
The reason why is that you've misspelled CET (not CEST)
Neither CET nor CEST are portable
On Apr 20, 2014, at 2:16 AM, Prof Brian Ripley wrote:
On 20/04/2014 08:50, Prof Brian Ripley wrote:
On 18/04/2014 21:46, David Winsemius wrote:
On Apr 18, 2014, at 12:59 PM, Prof Brian Ripley wrote:
On 18/04/2014 19:46, Rui Barradas wrote:
Hello,
The reason why is that you've
Thank you for your reply.
I discovered the OlsonNames() function to get the time-zone names in my
system. Rui get a warning message when using a not recognized tz. On my
system this doesn't succed.
I solved as follow:
dt1 = as.POSIXct(2014-04-18 09.00, format=%Y-%m-%d %H.%M, tz =
Europe/Rome)
I forgot:
sysname
release
Linux
3.5.0-48-generic
version
#72-Ubuntu SMP Mon Mar 10 23:18:29 UTC 2014
2014-04-19 14:03 GMT+02:00 Nicola Sturaro Sommacal
Hi.
I am new to POSIX and I'd like to understand the reason of this difference.
dt1 = as.POSIXct(2014-03-29 09.00, format=%Y-%m-%d %H.%M)
dt2 = as.POSIXct(2014-03-30 09.00, format=%Y-%m-%d %H.%M)
dt2-dt1
dt1[1] 2014-03-29 09:00:00 CET dt2[1] 2014-03-30 09:00:00 CEST dt2-dt1
Time difference of
Hello,
The reason why is that you've misspelled CET (not CEST)
dt1 = as.POSIXct(2014-04-18 09.00, format=%Y-%m-%d %H.%M, tz =
CEST)
Warning messages:
1: In strptime(x, format, tz = tz) : unknown timezone 'CEST'
2: In as.POSIXct.POSIXlt(as.POSIXlt(x, tz, ...), tz, ...) :
unknown timezone
On 18/04/2014 19:46, Rui Barradas wrote:
Hello,
The reason why is that you've misspelled CET (not CEST)
Neither CET nor CEST are portable time-zone names. We have not been
given the 'at a minimum' information required by the posting guide, so
please read ?Sys.timezone on your system.
On Apr 18, 2014, at 12:59 PM, Prof Brian Ripley wrote:
On 18/04/2014 19:46, Rui Barradas wrote:
Hello,
The reason why is that you've misspelled CET (not CEST)
Neither CET nor CEST are portable time-zone names. We have not been given
the 'at a minimum' information required by the
I have a data frame with variable datetime which is of class POSIXct.
Consecutive observations are separated by 30 minutes.
However, some of the differences reported by R give unexpected results.
For example consider the following two consecutive entries:
par.dat$datetime[5944]
[1] 2010-04-04
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
On Behalf Of David Fox
Sent: Tuesday, January 28, 2014 5:15 PM
To: r-help@r-project.org
Subject: [R] Difference between two datetimes
I have a data frame with variable datetime which
Dear all,
When I run an arima(1,1,1) on an I(1) variable, y, I get different estimates to
when I first difference the variable myself, e.g y2-diff(y), and then run
arima(1,0,1) on y2. Shouldn't these two approaches give the same output?
Any help will be much appreciated.
george
Dear all,
When I run an arima(1,1,1) on an I(1) variable, e.g. y, I get different
estimates to when I first difference the variable myself, e.g y2-diff(y),
and then run arima(1,0,1) on y2. Shouldn't these two approaches give the
same output?
Any help will be much appreciated.
george
--
View
Hi George: Assuming it's still relevant, the link below will explain why.
http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm
On Thu, Jul 18, 2013 at 2:14 PM, George Milunovich
george.milunov...@mq.edu.au wrote:
Dear all,
When I run an arima(1,1,1) on an I(1) variable, y, I get different
Hi Mark,
This is very helpful!!
Much appreciated
Sent from my iPad
On Jul 19, 2013, at 3:51 AM, Mark Leeds marklee...@gmail.com wrote:
Hi George: Assuming it's still relevant, the link below will explain why.
http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm
On Thu, Jul 18, 2013 at
Hi,
Does anybody know the difference between the Lloyd and Forgy algorithms
specified for R's kmeans clustering options? I know how Lloyd works, but I
cannot access Forgy's paper and could not find any specific information on
the web about how it really differs from Lloyd's method.
I appreciate
Hi,
A 5-second search on Internet brought me here:
http://en.wikibooks.org/wiki/Data_Mining_Algorithms_In_R/Clustering/K-Means
Regards,
Pascal
On 20/06/13 15:57, Safiye Celik wrote:
Hi,
Does anybody know the difference between the Lloyd and Forgy algorithms
specified for R's kmeans
Hi,
I searched for a long time and I read this website before asking the
question. But it does not answer my issue. Thanks anyway.
I digged unto the source code and realized that there is no difference
between the implementations of Lloyd and Forgy. In fact, in kmeans.R, the
method number is set
...@stat.math.ethz.ch
Subject: Re: [R] Difference between R and SAS in Corcordance index in ordinal
logistic regression
Please define 'mean probabilities'.
To compute the C-index or Dxy you need anything that is monotonically
related to the prediction of interest, including the linear combination
For lrm fits, predict(fit, type='mean') predicts the mean Y, not a
probability.
Frank
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and
lrm does some binning to make the calculations faster. The exact calculation
is obtained by running
f - lrm(...)
rcorr.cens(predict(f), DA), which results in:
C IndexDxy S.D. nmissing
0.96814404 0.93628809 0.0380833632.
Subject: Re: [R] Difference between R and SAS in Corcordance index in ordinal
logistic regression
lrm does some binning to make the calculations faster. The exact calculation
is obtained by running
f - lrm(...)
rcorr.cens(predict(f), DA), which results in:
C IndexDxy
differently ?
Thank for your help and best regards,
OC
Date: Thu, 24 Jan 2013 05:28:13 -0800
From:
f.harrell@
To:
r-help@
Subject: Re: [R] Difference between R and SAS in Corcordance index in
ordinal logistic regression
lrm does some binning to make the calculations faster. The exact
Hi!
as my subject says I am struggling with the different of a two-way ANOVA and
a (two-way) ANCOVA.
I found the following examples from this webpage:
http://www.statmethods.net/stats/anova.html
# One Way Anova (Completely Randomized Design)
fit - aov(y ~ A, data=mydataframe)
# Randomized
On Jul 4, 2012, at 15:20 , syrvn wrote:
Hi!
as my subject says I am struggling with the different of a two-way ANOVA and
a (two-way) ANCOVA.
I found the following examples from this webpage:
http://www.statmethods.net/stats/anova.html
# One Way Anova (Completely Randomized Design)
The usual terminology uses the number of ways to mean the number of
factors (categorical
or classification variables, with more than one degree of freedom per
factor).
The term covariate is used for continuous variables, with exactly one df.
On Wed, Jul 4, 2012 at 9:20 AM, syrvn ment...@gmx.net
On 25/05/2012 12:41 PM, QAMAR MUHAMMAD UZAIR wrote:
dear all,
it will just take you a minute to tell me the difference
between qnorm and qqnorm. are they same or is there any
difference between them??
They are very different, qqnorm draws a plot, qnorm does a calculation
of some of the values
-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf
Of brwin338
Sent: Thursday, May 03, 2012 4:33 PM
To: r-help@r-project.org
Subject: [R] Difference between 10 and 10L
Good Evening
We have been searching through the R documentation manuals without success on
this
one.
What
On Thu, May 03, 2012 at 07:32:46PM -0400, brwin338 wrote:
Good Evening
We have been searching through the R documentation manuals without success on
this one.
What is the purpose or result of the L in the following?
n=10
and
n=10L
or
c(5,10)
versus
c(5L,10L)
Hi.
The help page
Good Evening
We have been searching through the R documentation manuals without success on
this one.
What is the purpose or result of the L in the following?
n=10
and
n=10L
or
c(5,10)
versus
c(5L,10L)
Thanks
Joe
Thanks
Joe
[[alternative HTML version deleted]]
tibco.com
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf
Of brwin338
Sent: Thursday, May 03, 2012 4:33 PM
To: r-help@r-project.org
Subject: [R] Difference between 10 and 10L
Good Evening
We have been searching through the R
On 08.04.2012 20:39, Bazman76 wrote:
Hi there,
Can someone explain what the difference between spec.pgram and spec.ar is?
I understand that they attempt to do the same thing one using an AR
estimation of the underlying series to estimate teh sensity the other using
the FFT. However when
OK so I neeed to understan better what it it they are trying to measure.
I understood (incorrectly it seems) that they were simply different methods
to get the same result?
--
View this message in context:
On 09.04.2012 17:01, Bazman76 wrote:
OK so I neeed to understan better what it it they are trying to measure.
I understood (incorrectly it seems) that they were simply different methods
to get the same result?
Yes. Also note this is a mailing list and you are lucky I was able to
remember
On Apr 9, 2012, at 16:55 , Uwe Ligges wrote:
On 08.04.2012 20:39, Bazman76 wrote:
Hi there,
Can someone explain what the difference between spec.pgram and spec.ar is?
I understand that they attempt to do the same thing one using an AR
estimation of the underlying series to estimate
oops sorry
n 08.04.2012 20:39, Bazman76 wrote:
Hi there,
Can someone explain what the difference between spec.pgram and spec.ar is?
I understand that they attempt to do the same thing one using an AR
estimation of the underlying series to estimate teh sensity the other
using
the
Yes I agree, there may be something pathalogical in the way at least one of
the models handles the data. That's why I was trying to get a better handle
on how the two functions spec.prgm() and spec.ar() work.
The data has been processed by a wavelet analysis, so what you are seeing as
the raw
On Mon, Apr 9, 2012 at 9:27 AM, Bazman76 h_a_patie...@hotmail.com wrote:
Yes I agree, there may be something pathalogical in the way at least one of
the models handles the data. That's why I was trying to get a better handle
on how the two functions spec.prgm() and spec.ar() work.
The data
On 09/04/2012 18:52, Bert Gunter wrote:
On Mon, Apr 9, 2012 at 9:27 AM, Bazman76h_a_patie...@hotmail.com wrote:
Yes I agree, there may be something pathalogical in the way at least one of
the models handles the data. That's why I was trying to get a better handle
on how the two functions
Hi there,
Can someone explain what the difference between spec.pgram and spec.ar is?
I understand that they attempt to do the same thing one using an AR
estimation of the underlying series to estimate teh sensity the other using
the FFT. However when applied to teh same data set they seem to be
As I said before: please dput() some working data and I'll try to work
something up.
Without it, the only thing I can reasonably suggest is that perhaps
you are looking for the window() function to be applied before
min/max. Something like:
X - ts(1:48, start = 1, frequency = 4)
Y - ts(1:12,
Hello Michael,
Thanks again for your reply. Actually, I am working with wind data.
I have some sample data for actual load.
scan(/home/sam/Desktop/tt.dat) -tt ## This is the input for the actual
output of the generation
t = ts(tt, start=8, end=24, frequency=1,)
I have another random sequence
Hello,
Can you please help me with this? I am also stack in the same problem.
Sam
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It's not clear what it means for the differences to be of increasing
order but if you simply mean the differences are increasing, perhaps
something like this will work:
library(caTools)
X = cumsum( 2*(runif(5e4) 0.5) - 1) # Create a random Walk
Y = runmean(X, 30, endrule = mean, align = right)
Hello Michael,
Thanks for your reply. What I want to do is something like this? For
example, I have a continuous time series y=x(t), and another discrete time
series z=w(t).
Xdiff(i)=Max. difference between x(t) and w(t) in interval i
Ndiff(i)=Min. difference between x(t) and w(t) in interval
Can you post working examples of your data using the dput() function?
There are so many types of time series in R and so many different
things you could mean that it's just easier to work with real data.
Michael
On Tue, Nov 15, 2011 at 4:28 PM, Sarwarul Chy sarwar.sha...@gmail.com wrote:
Hello
Hallo
Can anyone tell me the difference between
foo$a[2] - 1 and foo[2,a] - 1 ?
I thought that both expressions are equivalent, but when I run the following
example, there is obviously a difference.
foo - data.frame(a=NA,b=NA)
foo
a b
1 NA NA
foo$a[1] - 1
foo$b[1] - 2
foo$a[2] - 1
Columns in data frames must all have the same number of elements. Your first
example attempts to violate that, because it works with a single column. The
second example works on the entire data frame, so it is able to lengthen the
other column to match.
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