[R] SVM, feature selection and parameter tuning

2008-10-23 Thread Stefan Koenig
Hi,

Does anyone know why the package MCRestimate is not part of the BioConductor 
2.2 anymore?

I am looking for package doing support vector machine analyses including (i) 
variable/feature selection and (ii) parameter tuning in one learning period.

Many thanks,

Stefan

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[R] SVM, feature selection and parameter tuning

2008-10-22 Thread Stefan Koenig
Hi,

Does anyone know why the package MCRestimate is not part of the BioConductor 
2.2 anymore?

I am looking for package doing support vector machine analyses including (i) 
variable/feature selection and (ii) parameter tuning in one learning period.

Many thanks,

Stefan

--

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and provide commented, minimal, self-contained, reproducible code.


[R] How to combine to PCAs

2008-06-05 Thread Stefan Koenig
Dear all:

Subjects were measured two times (t1 and t2) on different variables (v1 ... 
vn). 
Between t1 and t2 there was an experimental manipulation. I computed two PCAs 
for time-points t1 and t2. 

Is it possible to combine both PCAs in order to get only one set of 
eigenvectors? Due to the experimental manipulation measurement values on time 
points t1 and t2 changed for each subject.

Many thanks
Stefan
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[R] Regression Model with Memory

2008-06-02 Thread Stefan Koenig
Dear all:

I am searching for a regression model (e.g. y=Xb+e) in which dummy-coded events 
(to time point t) on different regressors in X exhibit an effect on subsequent 
responses in the vector y (to time-points t+1, t+2,… t+n). My aim is to 
estimate how long the memory effect is and how strong a certain event 
influences subsequent responses (whether the memory decays e.g. linear or 
exponentially). My first impression is that state-space models are appropriate. 
 However, according to my first understanding in these models regularities in 
the residuals are explained without using the knowledge of the event history. 
Or is a simple linear regression model with time-shifted regressors appropriate?

The response vector y includes misses and the events in X are sampled on 
irregular time points.

Many thanks
Stefan

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and provide commented, minimal, self-contained, reproducible code.


[R] Regression Model with a Memory Covariate Process

2008-05-31 Thread Stefan Koenig
Dear all:

I am searching for a regression model (e.g. y=Xb+e) in which dummy-coded events 
(to time point t) on different regressors in X exhibit an effect on subsequent 
responses in the vector y (to time-points t+1, t+2,… t+n). My aim is to 
estimate how long the memory effect is and how strong a certain event 
influences subsequent responses (whether the memory decays e.g. linear or 
exponentially). My first impression is that state-space models are appropriate. 
 However, according to my first understanding in these models regularities in 
the residuals are explained without using the knowledge of the event history. 
Or is a simple linear regression model with time-shifted regressors appropriate?

The response vector y includes misses and the events in X are sampled on 
irregular time points.

Many thanks
Stefan

-- 
Ist Ihr Browser Vista-kompatibel? Jetzt die neuesten

__
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 provide commented, minimal, self-contained, reproducible code.