3 months ago I asked Probability Mass Function making the Truncated Normal Discrete
I can't seem to get enough attention probably because of my poor wording.
I could use the distribution I asked for for a Bayesian prior but I wouldn't like the need to use Bayes' theorem to get my posterior everytime.
I'd rather assume that every random variable which is assumed to be normally distributed simply follows the generalisation (the discrete truncated normal) and then simply estimate the parametres (the Normal and Truncated Normal would be included as special cases which would mean that if the variable is trully normally or truncated normally distributed I would have no problems) I would first find out what transformations of the mean and the standard deviation the parametres (μ and σ) are, estimate the mean and the standard deviation (a, b and c should be known a priori) and then solve the equations (the transformations) to find my estimates for my parametres. And get my distribution (in the technical term) which describes the random variable (the distribution in the common, natural, colloquial term).
My question is
How could I word my main Question to attract views and answers?