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20 messages · Sajeeka Nanayakkara, Bert Gunter, R. Michael Weylandt +6 more

Rui Barradas
# 
Hello,

Inline.

Em 03-07-2012 09:22, Sajeeka Nanayakkara escreveu:
By reading the help page.

?arima

Value

[...]

code 	the convergence value returned by _optim_.

Hope this helps,

Rui Barradas
Rui Barradas
# 
Hello,

Sorry, but do you read the answers to your posts?
Inline.

Em 04-07-2012 08:02, Sajeeka Nanayakkara escreveu:
And I have already answered to a question starting like this yesterday. 
In the mean time, the subject line changed.
Yes, it was this question, the subject line was 'question'...

... And the answer was: read the manual, that I quoted, by the way.

It now changed to: read the manual, period.

Rui Barradas
5 days later
Rui Barradas
# 
Hello,

The function is

?Box.test

It has two types, Box-Pierce and Ljung-Box.

Hope this helps,

Rui Barradas

Em 09-07-2012 15:59, Sajeeka Nanayakkara escreveu:
8 days later
arun
# 
HI,

Check this link:
http://stackoverflow.com/questions/1444306/how-to-use-outlier-tests-in-r-code

Hope it would be helpful.
A.K.



----- Original Message -----
From: Sajeeka Nanayakkara <nsajeeka at yahoo.com>
To: "r-help at r-project.org" <r-help at r-project.org>
Cc: 
Sent: Wednesday, July 18, 2012 9:27 AM
Subject: [R] R code for to check outliers





?What is the R code to check whether data series have outliers or not?

Thanks,

Sajeeka Nanayakkara
??? [[alternative HTML version deleted]]


______________________________________________
R-help at 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 provide commented, minimal, self-contained, reproducible code.
R. Michael Weylandt
# 
To further what Bert says:

You would almost certainly prefer to use robust statistics than
"outlier detection".

I believe Greg Snow's TeachingDemos package has a data set "outliers"
suggesting some of the perils of doing things the outlier-removal way.

Best,
Michael
On Wed, Jul 18, 2012 at 9:14 AM, Bert Gunter <gunter.berton at gene.com> wrote:
S Ellison
# 
In case noone else has pointed you there, you could try the 'outliers' package. That contains some of the 'standard' methods of outlier testing for univariate data.

What you do with them when you find them is a rather more complicated and, as you have already seen, controversial question.

S Ellison

*******************************************************************
This email and any attachments are confidential. Any use...{{dropped:8}}
Duncan Murdoch
#
On 18/07/2012 10:14 AM, Bert Gunter wrote:
I think you are assuming that Sajeeka will handle the outliers 
incorrectly.   It happens often enough, but I don't think it's polite to 
make that assumption.

My answer to the question would have been to ask the question, "how do 
you define outliers?"  Certainly it's possible to define outliers in the 
context of a model, and their presence is an indication of problems with 
the model.  The correct response might be to weaken the assumptions of 
your model and use a robust procedure as Michael suggested (which might 
mean throwing away the outliers), or it might be to change the model in 
some other way.  Your advice to consult a subject matter expert is good, 
but in my experience, they often put more faith in their models than 
they should, so as a statistician, I think you should point out 
discrepancies like outliers.  Which means it's good to have a function 
to detect them.

Duncan Murdoch
Martin Maechler
# 
> checkforoutliers <- function(series) NULL 

  > Cheers, Bert

    > *Explanation: There is no such thing as a statistical
    > outlier -- or, rather,"outlier" is a fraudulent
    > statistical concept, defined arbitrarily and without
    > scientific legitimacy. The typical unstated purpose of
    > such identification is to remove contaminating or
    > irrelevant data, but such a judgment can only be made by a
    > subject matter expert with knowledge of the context and,
    > usually, the specific cause for the unusual data. Do not
    > be misled by the large body of statistical literature on
    > this topic into believing that statistical analysis alone
    > can provide objective criteria to do this. That is a path
    > to scientific purgatory.

    > For the record: 1. I am a statistician 
    > 2. Lots of highly knowledgeable, smart statisticians will condemn what I
    > have just said as stupid ranting.

I entirely agree with you that  outlier-removing
procedures are mostly misused, and dangerous because of that
misuse {and hence should typically NOT be taught, or not the way
I have seen them taught (on occasions, not here at ETH!)...}

and I even more fervently agree with Michael Weylandt's 
recommendation to use robust statistics rather than outlier
detection --- at least in those cases where "robust statistics"
is *not* ill-re-defined  as  {outlier detection}+{classical stats}.

However, I don't think 'outlier' to be a fraudulent concept.
Rather I think outliers can be pretty well defined along the
line of "outlier WITH RESPECT TO A MODEL" 
 (and 'model' means 'statistical model', i.e., with some
 randomness built in) :

    Outlier wrt model M := 
	  an observation which is highly
	  improbable to be observed under model M

(and "highly improbable" of course is somewhat vague, but that's
 not a problem per se.)
A version of the above is 

 Outlier := an observation that has unduely large influence on
	 the estimators/inference performed

where 'estimator / inference'  imply a model of course.

So I think outlier is a useful concept for those who think about
*models* (rather than just data sets), and I agree that without
an implicit or explicit model, "outlier" is not well defined.

    > The perils of a mailing list.
    > -- Bert

:-)

Martin
> On Wed, Jul 18, 2012 at 6:27 AM, Sajeeka Nanayakkara .. wrote:
>> 
    >> What is the R code to check whether data series have
    >> outliers or not?
    >> 
    >> Thanks,
    >> 
    >> Sajeeka Nanayakkara


    > -- 
    > Bert Gunter Genentech Nonclinical Biostatistics
Nordlund, Dan (DSHS/RDA)
# 
Sajeeka,

You have been given lots of good information and appropriate warnings.  Let me add another caveat to think about in the context of outliers/unusual values.  A value may only be unusual in a multivariate context.  If we have a dataset with human heights in it, a value of 73 inches would not be unusual.  If we then learned that this particular individual was female, it would be somewhat unusual but certainly within the realm of possibility.  If we then learn that the individual is 3 years old, it would be highly unusual.

So, you can see why people on the list are somewhat unwilling to say here is THE function "to check whether data series have outliers or not."

Now having said that, can you define what YOU mean by "outlier" and why you are concerned about finding them.  Someone may be able to offer advice that will help you achieve your goal.

Dan

Daniel J. Nordlund
Washington State Department of Social and Health Services
Planning, Performance, and Accountability
Research and Data Analysis Division
Olympia, WA 98504-5204
Rui Barradas
# 
Hello,

Inline

Em 18-07-2012 18:44, Nordlund, Dan (DSHS/RDA) escreveu:
Uma Thurman!
Agreeing with what has being said and not wanting to misdirect no one, 
there's a function in the graphics package that gives outliers, boxplot. 
They are computed based on boxplot.stats so see

?boxplot.stats

in particular the parameter coef and it's default value.
See also the return values from both these functions.

Rui Barradas
5 days later
arun
# 
Hi,

Possibly ?nnet package.
A.K.




----- Original Message -----
From: Sajeeka Nanayakkara <nsajeeka at yahoo.com>
To: "r-help at r-project.org" <r-help at r-project.org>
Cc: 
Sent: Tuesday, July 24, 2012 2:21 PM
Subject: [R] R functions to forecast using neural network

Is there any R functions to forecast, using feedforward bakpropagation algorithm in neural networks?

?
Sajeeka Nanayakkara
??? [[alternative HTML version deleted]]


______________________________________________
R-help at 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 provide commented, minimal, self-contained, reproducible code.
arun
# 
HI,

Another package might be neuralnet.? I never used it before.? So, I can't comment much on it.? Also, check this link (http://stackoverflow.com/questions/9062522/neural-network-in-r-to-predict-stock-return).

A.K.
Bert Gunter
# 
SEARCH!

Google on e.g. "neural nets R package"
... or search on Rseek.org

Check the CRAN Machine Learning task view

-- Bert

On Wed, Jul 25, 2012 at 11:01 AM, Sajeeka Nanayakkara
<nsajeeka at yahoo.com> wrote: