Update smsim-in-R.Rmd

First comments (before the "IPF in R")
I think more details could be to much, BUT there is an hypothesis for this theory that we "have to mention". I have to find the english formulation, but it consider that "without any contrary information, we can consider that each distribution have the same probability to appear. So, it take the one that represent the most of population."

Le Samedi 27 Décembre 2014 22:58 CET, Robin <notifitions@github.com> a écrit: 
 
> > @@ -57,7 +82,47 @@ This is *reweighting*.
> >  Regardless of implementation method,
> >  IPF can be used to allocate individuals to zones through the calculation
> >  of *maximum likelihood* values for each zone-individual combination represented
> > -in the wieght matrix.
> > +in the weight matrix.
> > +
> > +```{r, echo=FALSE}
> > +#(Dumont,2014) I am not sure it is really the maximum of likelihood... Perhaps the maximisation of entropy no?
> 
> I think the maximisation of entropy and maximum likelihood are similar, if not the same, concepts. Papers using the ML terminology include [this](http://linkinghub.elsevier.com/retrieve/pii/S019897150800080X) and [this](http://www.sciencedirect.com/science/article/pii/0167947393E00559). I've never fully understood maximum entropy either. Is it the values that maximise the number of ways that values can change a small amount while maintaining the same result? I don't think we need to go into too much detail on the theory. We should refer interested readers to more theoretical papers like this: http://www.sciencedirect.com/science/article/pii/0167947393E00559 and this: http://data.princeton.edu/wws509/notes/c5.pdf . I'm out of my depth here.
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