This is achieved by first generating an SPD for each phase and normalizing

mai 31, 2022 · Filed Under Furfling review · Commentaire 

This is achieved by first generating an SPD for each phase and normalizing

Theoretically, a calibrated date should be a continuous probability density function (PDF); however, in practice a date is represented as a discrete vector of probabilities corresponding to each calendar year, and is therefore a furfling real? probability mass function (PMF). This discretization (of both a proposed model probability distribution and a calibrated date probability distribution) provides the advantage that numerical methods can be used to calculate likelihoods.

Hypothetically, if a calibrated date was available with such precision that it could be attributed with certainty to just a single calendar year the model likelihood would trivially be the model probability at that date. Similarly, if the data comprised just two such point estimates (at calendar time points A and B), the model’s relative likelihood would trivially be the model probability at date A multiplied by the model probability at date B. Lire la suite