>
>
> and so on. Note that if you try to use RR (which is the same as
> RealField(53)) you run into the same precision/roundoff problem as you
> had before. Hence the need to increase the working precision.
>
> Also note that R.random_element() can only do uniform distribution, so
> if you were hoping for something fancier this won't help.
>
>
Yeah, since the RealDistribution code uses GSL with code like
elif self.distribution_type == gaussian:
result = gsl_ran_gaussian(self.r, self.parameters[0])
elif self.distribution_type == rayleigh:
result = gsl_ran_rayleigh(self.r, self.parameters[0])
elif self.distribution_type == lognormal:
result = gsl_ran_lognormal(self.r, self.parameters[0],
self.parameters[1])
elif self.distribution_type == pareto:
result = gsl_ran_pareto(self.r, self.parameters[0],
self.parameters[1])
elif self.distribution_type == t:
result = gsl_ran_tdist(self.r, self.parameters[0])
elif self.distribution_type == F:
where it's not clear that self.r passes on any precision information. That
would be good to change, but I'm not sure how easy that would be, assuming
it's possible for GSL to even take that into account in these functions.
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