I remember seeing an example using the EM algorithm where one of the variables
was age of child and they assumed that an age like 16 months was accurate to
the month, but ages like 18 months may have been off by as much as 2 months and
ages like 3 years could be off by 6 months (or more), so the
Hello,
@Bert: I didn't expect a full tutorial service but probably a hint of
the Masters of statistics ;)
Anyway I posted my question again on a special statistic
forum. Your hint about the censored regression: I don't think
that this is the case here. As so far as I understand it is there
the d
- Please also reply to the original poster who may not be subscribed to
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- Please cite the original question (and other relevant parts of the
thread) since some readers of this list will delete messages before an
answer arrives.
Uwe Ligges
On 17.07.2011 15:22, saskay wrote:
You cou
You could treat the dependent variable as a nominal variable. And scale the
indepent variables to have a Mean:0 and StDev:1. Stick all these in a
multinomial regression package such as mlogit. Or a non -parametric method
such as randomForest.
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Johannes:
R is not a statistical tutorial service, although kind and able
helpeRs sometimes do reply to such queries. You should try such a
service, for example:
http://stackoverflow.com/
FWIW, this is an example of censoring in regression. R has packages
for this, but you need to learn more or
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