Re: [R] - detecting outliers

2012-06-07 Thread Özgür Asar
Hi,

I believe that first learning the appropriate statistical methods to detect
the outliers and searching for the related functions in R is a better way.

Ozgur

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Re: [R] - detecting outliers

2012-06-07 Thread Rui Barradas

Hello,

Had you looked more, and you would have seen R-help discussions on what 
is an outlier. Almost unanimously, an ill defined concept.


In your problem, predators don't eat all eggs that they are given except 
for one case, 38 were given and all 38 were eaten. You can detect this 
in R with


boxplot.stats(d$FR)

Or with the return value of boxplot. See ?boxplot

Hope this helps,

Rui Barradas

Em 07-06-2012 07:24, Joachim Audenaert escreveu:

Hello all,

I am estimating parameters for regression functions on experimental data.
Functional response of Rogers type II.

I would like to know which points of my dataset are outliers. What is the
best method to do this with R?
I found a method via R help, but would like to know if there are better
methods for my purpose.
Here is the script I us now:

library("mvoutlier")
dat <- read.delim("C:/data.txt")
uni.plot(dat)

My data looks like the following (copied into a txt file):
(N0 is the initial number of eggs fed to the predator, FR is the number of
eggs eaten by the predator during 24h)

N0  FR
37  30
27  15
36  14
37  13
45  8
25  0
47  20
34  6
25  8
21  7
24  24
34  17
23  10
29  5
38  38
24  24
20  17
14  8
18  15
15  10
26  5
33  5
22  21
38  3
22  20
23  19
20  6
20  4
21  18
25  5
13  13
9   8
8   4
7   7
8   5
11  9


Kind regards,
Met vriendelijke groeten,
Joachim

Don't waste paper! Think about the environment before printing this e-mail

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Joachim Audenaert
Adviesdienst Gewasbescherming
Proefcentrum voor Sierteelt
Schaessestraat 18
B-9070 Destelbergen
Belgium
Tel. +32 9 353 94 71
Fax +32 9 353 94 95
E-mail: joachim.audena...@pcsierteelt.be
www.pcsierteelt.be
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Re: [R] - detecting outliers

2012-06-07 Thread Ben Bolker
Joachim Audenaert  pcsierteelt.be> writes:

> 
> Hello all,
> 
> I am estimating parameters for regression functions on experimental data. 
> Functional response of Rogers type II.
> 
> I would like to know which points of my dataset are outliers. What is the 
> best method to do this with R?

  The best method for detecting outliers really depends on the
motivation/purpose.  Your data look noisy, but by eye nothing
really jumps out.  Looking at a histogram (hist()) and Q-Q plot
qqnorm() of the residuals of the fit, it looks like the distribution
is slightly skewed but that there are no points that really fall
very far outside a normal distribution (normality is not a necessity
for making inferences from an nls fit, but it helps a lot)

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[R] - detecting outliers

2012-06-06 Thread Joachim Audenaert
Hello all,

I am estimating parameters for regression functions on experimental data. 
Functional response of Rogers type II.

I would like to know which points of my dataset are outliers. What is the 
best method to do this with R?
I found a method via R help, but would like to know if there are better 
methods for my purpose. 
Here is the script I us now:

library("mvoutlier")
dat <- read.delim("C:/data.txt")
uni.plot(dat)

My data looks like the following (copied into a txt file):
(N0 is the initial number of eggs fed to the predator, FR is the number of 
eggs eaten by the predator during 24h)

N0  FR
37  30
27  15
36  14
37  13
45  8
25  0
47  20
34  6
25  8
21  7
24  24
34  17
23  10
29  5
38  38
24  24
20  17
14  8
18  15
15  10
26  5
33  5
22  21
38  3
22  20
23  19
20  6
20  4
21  18
25  5
13  13
9   8
8   4
7   7
8   5
11  9


Kind regards,
Met vriendelijke groeten,
Joachim

Don't waste paper! Think about the environment before printing this e-mail

__

Joachim Audenaert
Adviesdienst Gewasbescherming
Proefcentrum voor Sierteelt
Schaessestraat 18
B-9070 Destelbergen
Belgium
Tel. +32 9 353 94 71
Fax +32 9 353 94 95
E-mail: joachim.audena...@pcsierteelt.be
www.pcsierteelt.be
__
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and provide commented, minimal, self-contained, reproducible code.