ABSTRACT
The methods discussed in Chapter 4 and Chapter 5 are in the vein of the frequentist school. The inference on the QTL location and effect is essentially based on the likelihood function of the unknowns under a formulated model. The unknowns are treated as fixed parameters. The Bayesian methods which we are discussing in this chapter are in a different vein. In the Bayesian approach, all the unknowns are considered as random variables. The inference is based on the posterior distribution of the unknowns which summarizes all the available information including those provided by the prior distribution and by the data through the likelihood function; see § 2.7.
