Update smsim-in-R.Rmd

First comments (before the "IPF in R")
No problem, I agree, this is more appropriate.

Le Samedi 27 Décembre 2014 22:36 CET, Robin <notifications@github.com> a écrit: 
 
> > +
> > +There are a wide range of possible methods to proceed to a spatial microsimulation. As with the majority of statistical 
> > +analyses, there are *deterministic* methods, characterized by the fact that it is completely determine, so no random
> > +or probabilistic numbers are used. In the other side, some *stochastic* methods consist in selecting a random number 
> > +in a specific distribution. For example, if we had no information about the zone's distribution but just the 
> > +total number of inhabitant in the zone, we could consider that
> > +the distribution of the sample is the distribution of the whole population. So, each individual will be chosen 
> > +randomly inside the individual in the sample. In this case, the distribution of the whole population will be
> > +asymptotically the one of the sample. 
> > +
> > +With stochastic methods, the intervention of a random function involves that executing two times the same algorithm
> > +could result in two different solution. To avoid it, we have to fix the *seed* of the random function. However,
> > +with these methods, we have to really trust the random function used. Note that it is impossible for a computer to
> > +effectively choose randomly a number, so there are existing algorithm to have *pseudo-random numbers*. The quality
> > +of this function has to be taken into account when proceeding to this kind of spatial microsimulation.
> > +
> 
> I think the terminology of 'random number generation' (RNG) is more appropriate here - see https://stat.ethz.ch/R-manual/R-devel/library/base/html/Random.html
> 
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