Extend list of supported distribution PDF shapes

[shunt16]

From Zhav Loizeau in #1:

Why name the uniform distribution rectangular and not uniform?
Wikipedia has a helpful selection (as always).

I would say some “most have” are:

• Exponential (for aging-free survival times, and generally positive-valued rv’s)
• Binomial distribution (for discrete-valued rv’s)
• Poisson distribution (for point processes)
• Categorical distribution, and multinomial distribution for classification

I understand that you assume mean 0 and, in the uniform and gaussian case, all you need is the variance parameter stored in the uncertainty variable to completely characterise the distribution. What happens for families of distributions with more parameters?

So tasks would be:

• Rename "rectangular" to "uniform"
• Add additional distributions
• Reference wikipedia list as the source?
• Add means to enable pdf_shape parameters

[shunt16]

Are there distributions we can imagine supporting that would require more parameters than the variance (uncertainty)? Is there an approach to this defined in the GUM?

If possible, my suggestion would be to avoid these for simplicity (implementation might take quite a significant generalisation of what we have so far and overcomplicate for users...)