Displaying 11 results from an estimated 11 matches for "tutzing".
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futzing
2012 Jan 25
1
What happened to the mirrors?
...esterday. According to http://mirror-status.centos.org a
whopping number of 227 mirrors are currently out of date. This is the
major part of all European mirrors. :(
Can someone please have a closer look at this?
Thanks a lot and regards
Patrick
--
Lobster LOGsuite GmbH, Hauptstra?e 67, D-82327 Tutzing
HRB 178831, Amtsgericht M?nchen
Gesch?ftsf?hrer: Dr. Martin Fischer, Rolf Henrich
2005 Jun 04
2
glm with a distribution free family
Dear R users,
I am trying to fit a glm with a distribution free family, link = log and variance = constant*mu. I guess I have to use the quasi family but the choices of variance are restricted to constant or mu or mu^2..., I don't know the way to choose the variance that I need, i.e. constant*mu.
If you have any ideas or advice, please tell me.
Thanks,
Laetitia Mestdagh
Laetitia Mestdagh
2008 Aug 19
4
spatial probit/logit for prediction
Hello all,
I am wondering if there is a way to do a spatial error probit/logit model in R? I can't seem to find it in any of the packages. I can do it in MATLAB with Gibbs sampling, but would like to confirm the results. Ideally I would like to use this model to predict probability of parcel conversion in a future time period. This seems especially difficult in a binary outcome model
2005 Jun 02
1
glm with variance = mu+theta*mu^2?
How might you fit a generalized linear model (glm) with variance =
mu+theta*mu^2 (where mu = mean of the exponential family random variable
and theta is a parameter to be estimated)?
This appears in Table 2.7 of Fahrmeir and Tutz (2001) Multivariate
Statisticial Modeling Based on Generalized Linear Models, 2nd ed.
(Springer, p. 60), where they compare "log-linear model fits to
2006 Feb 01
1
glm-logistic on discrete-time methods with individual and aggregated data
Dear R-Users,
without going into details I tried to prepare a simple example to show
you where I would need help.
In particular I prepare two examples-template for a study I'm conduction
on discrete-time methods for survival analysis.
Each of this example has two datasets which are basically equal, with
the exception that in the former one has individual data and in the
latter one aggregated
2008 Jul 10
0
ppls: version 1.02 including a new data set
Dear R users,
an update of the package ppls - Penalized Partial Least Squares - is now
available on CRAN.
It implements the methods described in
N. Kr?mer, A.-L. Boulesteix, G. Tutz
"Penalized Partial Least Squares with Applications to B-Spline
Transformations and Functional Data"
Chem. Intell. Lab. Sys. 2008
http://dx.doi.org/10.1016/j.chemolab.2008.06.009
Features of the package
2008 Jul 10
0
ppls: version 1.02 including a new data set
Dear R users,
an update of the package ppls - Penalized Partial Least Squares - is now
available on CRAN.
It implements the methods described in
N. Kr?mer, A.-L. Boulesteix, G. Tutz
"Penalized Partial Least Squares with Applications to B-Spline
Transformations and Functional Data"
Chem. Intell. Lab. Sys. 2008
http://dx.doi.org/10.1016/j.chemolab.2008.06.009
Features of the package
2011 Dec 21
1
semanage
Folks,
Should semanage be part of the policycoreutils package? At least in
6.x, it's not.
mark
2005 Jul 22
0
useR! 2006
We are happy to announce that the second R user conference
useR! 2006
is scheduled for June 15-17 2006 and will take place at the Vienna
University of Economics and Business Administration.
This second world-meeting of the R user community will focus on
- R as the `lingua franca' of data analysis and statistical computing,
- providing a platform for R users to
2005 Jul 22
0
useR! 2006
We are happy to announce that the second R user conference
useR! 2006
is scheduled for June 15-17 2006 and will take place at the Vienna
University of Economics and Business Administration.
This second world-meeting of the R user community will focus on
- R as the `lingua franca' of data analysis and statistical computing,
- providing a platform for R users to
2007 Oct 01
0
Interpretation of residual variance components and scale parameters in GLMMs
Dear R-listers,
I am working with generalized linear mixed models to quantify the
variance due to two nested random factors, but have hit a snag in the
interpretation of variance components. Despite my best efforts with
Venables & Ripley 2002, Fahrmeir & Tutz 2001, R-help archives, Google,
and other eminent sources (i.e. local R gurus), I have not been able
to find a definitive answer