[R] Logistic Regression Fitting with EM-Algorithm

[Robin Aly]

Dear Ted,

sorry for being unclear. Let me try again.

I indeed have no knowledge about the value of the response variable for 
any object.
Instead, I have a data frames of explanatory variables for
each object. For example,

     x1       x2       x3
1   4.409974 2.348745 1.9845313
2   3.809249 2.281260 1.9170466
3   4.229544 2.610347 0.9127431
4   4.259644 1.866025 1.5982859
5   4.001306 2.225069 1.2551570
...

, and I want to model a regression model of the form y ~ x1 + x2 + x3.

 From prior information I know that all coefficients are approximately 
Gaussian distributed around one and the same for the intercept around 
-10. Now I think there must be a package which estimates the 
coefficients more precisely by fitting the logistic regression function 
to the data without knowledge of the response variable (similar to 
fitting Gaussians in a mixture model where the class labels are unknown).

I looked at the flexmix package but this seems to "only" find 
dependencies in the data assuming the presence of some training data.
I also found some evidence In Magder1997 (see below) that such an 
algorithm exists, however from the documented math I can't apply the 
method to my problem.

Thanks in advance,
Best Regards
Robin

Magder, L. S. & Hughes, J. P. Logistic Regression When the Outcome Is 
Measured with Uncertainty American Journal of Epidemiology, 1997, 146, 
195-203




On 01/04/2011 12:36 AM, (Ted Harding) wrote:
> On 03-Jan-11 14:02:21, Robin Aly wrote:
>> Hi all,
>> is there any package which can do an EM algorithm fitting of
>> logistic regression coefficients given only the explanatory
>> variables? I tried to realize this using the Design package,
>> but I didn't find a way.
>>
>> Thanks a lot&  Kind regards
>> Robin Aly
> As written, this is a strange question! You imply that you
> do not have data on the response (0/1) variable at all,
> only on the explanatory variables. In that case there is
> no possible estimate, because that would require data on
> at least some of the values of the response variable.
>
> I think you should explain more clearly and explicitly what
> the information is that you have for all the variables.
>
> Ted.
>
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> E-Mail: (Ted Harding)<ted.harding at wlandres.net>
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> Date: 03-Jan-11                                       Time: 23:36:56
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