[R] missing data imputation - simulation

2008-06-04 Thread Birgitle

My dataset contains missing data and I would like to do something like an EM
algorithm or a Markov Chain Monte Carlo approach to get rid of the missing
data.

Is there a function for imputation or simulation of missing data apart from
those in the randomForest library?

Thanks in advance

Birgit

-
The art of living is more like wrestling than dancing.
(Marcus Aurelius)
-- 
View this message in context: 
http://www.nabble.com/missing-data-imputation---simulation-tp17642736p17642736.html
Sent from the R help mailing list archive at Nabble.com.

__
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.


Re: [R] missing data imputation - simulation

2008-06-04 Thread Chuck Cleland

On 6/4/2008 5:32 AM, Birgitle wrote:

My dataset contains missing data and I would like to do something like an EM
algorithm or a Markov Chain Monte Carlo approach to get rid of the missing
data.

Is there a function for imputation or simulation of missing data apart from
those in the randomForest library?

Thanks in advance

Birgit


RSiteSearch(imputation, restrict=functions)

RSiteSearch({multiple imputation}, restrict=functions)

  return many relevant hits.


-
The art of living is more like wrestling than dancing.
(Marcus Aurelius)


--
Chuck Cleland, Ph.D.
NDRI, Inc. (www.ndri.org)
71 West 23rd Street, 8th floor
New York, NY 10010
tel: (212) 845-4495 (Tu, Th)
tel: (732) 512-0171 (M, W, F)
fax: (917) 438-0894

__
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.


Re: [R] missing data imputation - simulation

2008-06-04 Thread Ulrike Grömping

Birgit,

not knowing your data, I would recommend R-package mice or function
aregImpute from R-package Hmisc as good multi-purpose tools.

Regards, Ulrike

-- 
View this message in context: 
http://www.nabble.com/missing-data-imputation---simulation-tp17642736p17643601.html
Sent from the R help mailing list archive at Nabble.com.

__
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.


Re: [R] missing data imputation - simulation

2008-06-04 Thread Birgitle

Many thenks to both of you:
Will have a look.

Birgit


Chuck Cleland wrote:
 
 On 6/4/2008 5:32 AM, Birgitle wrote:
 My dataset contains missing data and I would like to do something like an
 EM
 algorithm or a Markov Chain Monte Carlo approach to get rid of the
 missing
 data.
 
 Is there a function for imputation or simulation of missing data apart
 from
 those in the randomForest library?
 
 Thanks in advance
 
 Birgit
 
 RSiteSearch(imputation, restrict=functions)
 
 RSiteSearch({multiple imputation}, restrict=functions)
 
return many relevant hits.
 
 -
 The art of living is more like wrestling than dancing.
 (Marcus Aurelius)
 
 -- 
 Chuck Cleland, Ph.D.
 NDRI, Inc. (www.ndri.org)
 71 West 23rd Street, 8th floor
 New York, NY 10010
 tel: (212) 845-4495 (Tu, Th)
 tel: (732) 512-0171 (M, W, F)
 fax: (917) 438-0894
 
 __
 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.
 
 


-
The art of living is more like wrestling than dancing.
(Marcus Aurelius)
-- 
View this message in context: 
http://www.nabble.com/missing-data-imputation---simulation-tp17642736p17644180.html
Sent from the R help mailing list archive at Nabble.com.

__
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.