When it says 'matrix' it means it, not 'data frame'.
On Wed, 30 May 2007, Allan Clark wrote:
hello all
i would like to perform multiple imputation using the norm library.
but i seem to get the following error when i use the da.norm function.
Error in as.double.default(list(V1 =
Hi
On 22 Apr 2006 at 23:29, Bob Green wrote:
Date sent: Sat, 22 Apr 2006 23:29:02 +1000
To: r-help@stat.math.ethz.ch
From: Bob Green [EMAIL PROTECTED]
Subject:[R] Missing values detected when there are no missing
values
I am
At 11:11 7/10/2005, you wrote:
Hi,
I have the problem that for the step procedure stops due to missing
values. There are no options in Step or stepAIC to handle missing
values. Is there any way to run stepwise modelselection in R in an
automated way in this case?
Here is the last step before it
On Fri, 7 Oct 2005, Andreas Cordes wrote:
I have the problem that for the step procedure stops due to missing
values. There are no options in Step or stepAIC to handle missing
values. Is there any way to run stepwise modelselection in R in an
automated way in this case?
Try the hint it gives
On 6/6/2005 9:52 AM, Rolf Turner wrote:
I wish to pass a vector ``y'', some of whose entries are NAs to a
fortran subroutine which I am dynamically loading and calling by
means of .Fortran(). The subroutine runs through the vector entry by
entry; obviously I want to have it do one thing if y[i]
Hello,
Thanks for the instructive responses. But two questions arise.
Firstable I can't manage to load the library mice.
I'm using R 2.0.1 on my Debian
I try just copying the package in my library /usr/lib/R/library .
but when i do library()
...
mice
PROTECTED] De la part de Giordano Sanchez
Envoyé : mardi 26 avril 2005 11:58
À : r-help@stat.math.ethz.ch
Objet : Re: [R] missing values
Hello,
Thanks for the instructive responses. But two questions arise.
Firstable I can't manage to load the library mice.
I'm using R 2.0.1 on my Debian
I try just
On 04/26/05 09:58, Giordano Sanchez wrote:
Hello,
Thanks for the instructive responses. But two questions arise.
Firstable I can't manage to load the library mice.
I'm using R 2.0.1 on my Debian
The package called norm also has functions for missing data.
When I tried it, the values it gave
Jonathan Baron wrote:
On 04/26/05 09:58, Giordano Sanchez wrote:
Hello,
Thanks for the instructive responses. But two questions arise.
Firstable I can't manage to load the library mice.
I'm using R 2.0.1 on my Debian
The package called norm also has functions for missing data.
When I tried
On 26-Apr-05 Jonathan Baron wrote:
On 04/26/05 09:58, Giordano Sanchez wrote:
Hello,
Thanks for the instructive responses. But two questions arise.
Firstable I can't manage to load the library mice.
I'm using R 2.0.1 on my Debian
The package called norm also has functions for
Dear Giordano,
Library Hmisc, by Frank Harrell, contains several functions for imputation
which I have found extremely useful.
Best,
R.
On Tuesday 26 April 2005 11:58, Giordano Sanchez wrote:
Hello,
Thanks for the instructive responses. But two questions arise.
Firstable I can't manage
On 04/26/05 12:54, Ted Harding wrote:
Would you be kind enough to give sufficient detail to reproduce
such a case? I've used 'norm' (and 'cat' and 'mix') quite
extensively, without encountering non-sensible results (at any
rate in situations where the packages were not being abused,
which
Turns out that this is not a simple question. Depending on what
you want to do, some statistical methods will just deal with
missing data and use what is available, in different ways, e.g.,
cor(). For other purposes, you might want to impute (fill in)
the missing values, and then there are many
Hello,
The mice package http://web.inter.nl.net/users/S.van.Buuren/mi/hmtl/mice.htm
is also potentially interesting.
It works with R 1.9 but not always with newer versions.
Best regards,
Bruno
Bruno Falissard
Département
Avril Coghlan [EMAIL PROTECTED] writes:
Dear R help list,
I am trying to do a logistic regression
where I have a categorical response variable Y
and two numerical predictors X1 and X2. There
are quite a lot of missing values for predictor X2.
eg.,
Y X1 X2
red 0.6 0.2*
On 29 Oct 2004, Avril Coghlan wrote:
Dear R help list,
I am trying to do a logistic regression
where I have a categorical response variable Y
and two numerical predictors X1 and X2. There
are quite a lot of missing values for predictor X2.
eg.,
Y X1 X2
red 0.6 0.2*
On 29-Oct-04 Avril Coghlan wrote:
Dear R help list,
I am trying to do a logistic regression
where I have a categorical response variable Y
and two numerical predictors X1 and X2. There
are quite a lot of missing values for predictor X2.
eg.,
Y X1 X2
red 0.6 0.2*
red
(Ted Harding) wrote:
On 29-Oct-04 Avril Coghlan wrote:
Dear R help list,
I am trying to do a logistic regression
where I have a categorical response variable Y
and two numerical predictors X1 and X2. There
are quite a lot of missing values for predictor X2.
eg.,
Y X1 X2
red 0.6 0.2*
Anne Piotet wrote:
What R functionnalities are there to do missing values imputation
(substantial proportion of missing data)? I would prefer to use
maximum likelihood methods ; is the EM algorithm implemented? in
which package?
The so-called ``EM algorithm'' is ***NOT*** an
From: Rolf Turner
Anne Piotet wrote:
What R functionnalities are there to do missing values imputation
(substantial proportion of missing data)? I would prefer to use
maximum likelihood methods ; is the EM algorithm implemented? in
which package?
The so-called ``EM
On 12-May-04 Rolf Turner wrote:
Anne Piotet wrote:
What R functionnalities are there to do missing values imputation
(substantial proportion of missing data)? I would prefer to use
maximum likelihood methods ; is the EM algorithm implemented? in
which package?
The so-called ``EM
That's not an algorithm. It is a recipe for deriving an algorithm.
algorithm - A detailed sequence of actions to perform to accomplish some
task. Named after an Iranian mathematician, Al-Khawarizmi.
Technically, an algorithm must reach a result after a finite number of
steps, thus
(Ted Harding) [EMAIL PROTECTED] writes:
On 12-May-04 Rolf Turner wrote:
Anne Piotet wrote:
What R functionnalities are there to do missing values imputation
(substantial proportion of missing data)? I would prefer to use
maximum likelihood methods ; is the EM algorithm implemented? in
Picky, picky.
Details are in the eyes of the beholder.
Prof Brian Ripley [EMAIL PROTECTED] writes:
That's not an algorithm. It is a recipe for deriving an algorithm.
algorithm - A detailed sequence of actions to perform to accomplish some
task. Named after an Iranian mathematician,
A.J. Rossini wrote:
Picky, picky.
Details are in the eyes of the beholder.
algorithm - A detailed sequence of actions to perform to accomplish some
task. Named after an Iranian mathematician, Al-Khawarizmi.
Personally I like the first definition of 'Algorism, Algorithm' in the
1913 Websters
On 12-May-04 A.J. Rossini wrote:
(Ted Harding) [EMAIL PROTECTED] writes:
[...]
Algorithm, this, or not
[...]
Thanks, Ted :-) -- to extend it a bit, one can imagine the use of
approximate solutions to the 2 steps (simulation methods to get
expected values, similar range of approaches for
Thanks Brian.
The EM algorithm requires an ``E'' step and an ``M'' step. Harding
and Rossini appear to be seriously suggesting that an R function
could be written which would
(a) Perform the E step in arbitrary contexts, and
(b) For that given expected value, work out a
Rolf Turner [EMAIL PROTECTED] writes:
The EM algorithm requires an ``E'' step and an ``M'' step. Harding
and Rossini appear to be seriously suggesting that an R function
could be written which would
(a) Perform the E step in arbitrary contexts, and
(b) For that given expected
On 12-May-04 Rolf Turner wrote:
The EM algorithm requires an ``E'' step and an ``M'' step. Harding
and Rossini appear to be seriously suggesting that an R function
could be written which would
(a) Perform the E step in arbitrary contexts, and
(b) For that given expected value,
On Sun, 11 Apr 2004 23:37:22 -0400
[EMAIL PROTECTED] wrote:
Hi everyone,
I'm analysing a survival analysis data set at the moment with missing
values in the covariate and survival vectors (I have about 60
variables). I know there are some functions on the CRAN network to
deal with
Thanks. I was able to use na.omit to remove NAs. But it seems to me this
kills one of the advantages of the original algorithm for handling
missing values.
On Tue, 2004-04-06 at 11:54, Uwe Ligges wrote:
zhu wang wrote:
Dear helpers,
I am trying to use the mda package downloaded from
Package mda covers many things, including bruto, mars, polyreg and mda
itself. Which `the original algorithm' for which option did you have in
mind? More concretely, what where you trying to do with the package?
Given that the package is the original authors' own code, it seems
unlikely that
to NAs and I could not find
any option to handle missing values.
Zhu Wang
-Original Message-
From: Prof Brian Ripley [mailto:[EMAIL PROTECTED]
Sent: Fri 4/9/2004 12:53 PM
To: Wang, Zhu
Cc: Uwe Ligges; [EMAIL PROTECTED]; [EMAIL PROTECTED]
Subject:Re: [R] missing
On Fri, 9 Apr 2004, Wang, Zhu wrote:
I basically wanted to use MARS to reproduce results using the dataset
Marketing in the following book
http://www-stat-class.stanford.edu/~tibs/ElemStatLearn/
The authors actually provided S-Plus functions for mars, bruto ,etc. I
used all default
zhu wang wrote:
Dear helpers,
I am trying to use the mda package downloaded from the R website, but
the data set has missing values so I got an error message. Should I
manually handle these missing values? I was trying to read the documents
to specify any option related to missing
Grace Conlon [EMAIL PROTECTED] writes:
How can I deal with missing values in the excel file?
I used read.csv to imports data, how ever there are missing values in the csv file.
When I use names(), it turns out a error message: names attribute must be the same
length as the vector
What
mgcv 0.9 will handle missing values properly (provided you are happy that
dropping them is 'proper'). There is a pre-release version at:
www.stats.gla.ac.uk/~simon/simon/mgcv.html
(it is a pre-release version, so there will be bugs, reports of which
gratefully received!)
simon
Thank you for
On Wed, 28 May 2003, Adrian Dusa wrote:
I would like values 97, 98 and 99 to be treated as missing values.
VAR1[VAR1 %in% c(97,98,99)]-NA
-thomas
__
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
38 matches
Mail list logo
